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Gathid Debuts its Patented Identity Model - Gathid

Gathid — Thu, 08 Oct 2026 22:26:12 GMT

Enterprise Times U.K.

Gathid has debuted its patented Identity Model. It claims that this sets a new identity and access governance standard. It is built on a directed graph model. The company says this means it can deliver a secure, scalable identity in days, not months.

Peter Hill, Founder and CEO of Gathid, said, “While deploying our physical access security products for some of the world’s largest companies, including five of the Fortune 500’s top 50 companies, we saw firsthand how much identity debt most organizations carry.

“We realized organizations that are not as mature as these industry giants didn’t have the resources to effectively identify who has access to what and – more importantly – whether they should have access at all. This inspired us to invent a solution that helps organizations strengthen access management without completely overhauling their people, processes, physical infrastructure, and technology.”

How is Gathid redefining the IAM problem?

One of the biggest challenges in Identity & Access Management (IAM) is visibility. Talk about access control and most people think about individual and group access. Yet, these make up an ever-decreasing percentage of the objects that have access and permissions inside our organisations.

What Gathid is doing comes from its name – Gath(ered) id(entities). It identifies everything from individuals to groups, software, machines, printers, scanners, cameras, IoT, services accounts, and basically any object with rights and access inside an environment. Just identifying them is nothing new. Most directory service solutions, such as Active Directory, already do that.

Gathid differs in how it enumerates and articulates what each of those objects has access to and how they relate to each other. It does that through graph database technology, using what it calls a directed graph model. The model is not just simple to deploy but incredibly fast when it comes to identifying connections.

Importantly, it is also scalable. It is not something that is necessarily simple with graph technology. As an organisation grows, so does its complexity. Objects will have access to other objects and often inherit rights, access and permissions from them.

Tracing why an object, be that a person or otherwise, has access to something due to its interaction with groups and other objects has always been a major challenge. Gathid claims that is no longer the case. It means that when access to something is removed from an individual, for example, you can see its impact. It removes, or at least severely mitigates, the risk of a user losing access to something critical to their job.

What benefits is Gathid claiming?

Gathid has listed a number of key benefits for its directed identity model. They include:

Identity graph technology: Gathid’s patented approach creates a daily identity graph model. Enabling the constructed representation of virtual data relationships between identities and access rights to systems. This provides a comprehensive and holistic view of the entire enterprise identity landscape.
Rapid deployment: Gathid offers a streamlined, easy-to-deploy solution that receives and models data from digital, operational technology (OT). And physical access control systems (PACS) without requiring admin rights or complex bi-directional integration. Gathid delivers immediate insights and ROI, unlike the traditional approach of integrating all the disparate systems together. Which can take months or years to design and implement.
Affordable insight for every system: Gathid bridges the accessibility gap in identity governance. Offering scalable solutions tailored for organizations of all sizes. It can analyze role-based access and role mining for any system. Including legacy, air-gapped, or specialized systems, without the high costs of traditional approaches, which often include large consulting projects.
Toxic role combination alerts: Gathid’s advanced algorithms can analyze data across diverse technologies and detect instances where identities have risky access privileges that violate security and compliance policies. This allows organizations to identify and rectify toxic role combinations, creating a meaningful and accurate identity overview.
Incident memory: Gathid empowers incident response with a historical record of identity security alterations, allowing for a detailed review of access rights changes before, during, and after an incident. It can also provide alerts and recommendations for mitigating and preventing future incidents.
Compatibility: The Gathid platform is completely independent of existing enterprise applications and can receive simple identity-related data from all systems, either manually or automatically. Gathid does not attempt to maintain concurrency of its identity model, simply receiving daily identity data to form its daily identity graph model and then archiving the model the following day when a new model will be created from fresh data feeds.

Enterprise Times: What does this mean?

Access permission bloat is a thing. Stay at a company for any length of time and hold more than one role, and you will see your permissions increase. When people change roles, they are left with access for a period of time to facilitate handover. However, they are then rarely stripped of those accesses.

One reason is that people forget to take them away. The other is that often, nobody has a clue what accesses are really required for a particular role. It leads to people having rights and permissions they don’t need. When they are compromised, it makes it easy for cybercriminals to access other parts of the business.

The ability to see what a person has is a major step forward in IAM. However, it assumes that organisations are willing to use Gathid’s solution and invest in acting on what it shows.

Even more important is that this goes beyond people. It deals with every object that has access to an organisation. While there are solutions out there that already give greater visibility to the interconnectedness of objects, Gathid has gone further.

It will be interesting to see how quickly Gathid moves to provide case studies to show the impact of its technology. If it can engage security teams and show them what it offers, then there is a place for it in their tools. From an incident management and forensic analysis of an attack, it could be invaluable.

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AI Agents As A Line Item: Managing Machine Identity As A CFO Control - Gathid

Gathid — Thu, 08 Oct 2026 22:26:12 GMT

AI agents are no longer a pilot; they’re a line item. Service accounts, automation scripts and machine identities now create vendors, approve payments and touch source code. If we can’t see and govern what they can do, that’s not just an IT risk; it is a liability that can’t be valued.

Finance leaders should treat non-human access like payroll: reconciled daily, owned and auditable, so that automation accelerates value without inflating exposure.

Why Identity Is A CFO Control

When a payment bot can create vendors and release funds, its entitlements are a cash control. When a data pipeline can redact or enrich records, its privileges influence revenue recognition and compliance. When a build system can sign code, its keys represent brand integrity.

Insider fraud, supply chain attacks and privacy penalties often travel through over-privileged or orphaned non-human identities, especially when “temporary” access becomes permanent.

The Inventory Problem You Can’t Audit

In my experience, most companies can’t answer three basic questions:

How many non-human identities exist?
Who owns them?
What can they do?

Service accounts proliferate in cloud and OT; API tokens live in SaaS application settings no one remembers configuring. Spreadsheets and quarterly campaigns won’t solve a problem that changes daily. Finance needs a control surface that updates at the pace of the systems it governs.

Build A Living Map Of Access

The answer is a living, navigable model of people, systems and entitlements, reconciled to HR for humans and to accountable owners for machines. Think of it as an identity knowledge graph rebuilt every day: It discovers new agents, links them to workloads and traces what they can touch. For finance, this enables continuous measurement of exposure and the ability to simulate changes.

Design SoD For Machines

We are comfortable with segregation of duties for humans. However, we rarely apply the same rigor to automation. Start with cross-domain conflicts like “create supplier” and “release payment,” “promote code” and “sign binaries,” “modify ledger rules” and “post journals.” Define compensating controls where strict separation isn’t feasible. Make exceptions visible, time-boxed and owned. With a daily graph, conflicts can’t hide.

Treat Life Cycle Like Headcount

Bots should have the same joiner-mover-leaver discipline that is applied to employees. Define an owner and sponsor, require a business justification and set an end date. Rotate keys on a schedule that matches criticality. When a service scales out, review identities dynamically with least privilege; when it scales back, retire them. The digital twin should verify changes and reopen tickets when a revoke fails, or a permission reappears.

Create An 'Access P&L'

CFOs need metrics that move decisions. These could be:

Reconciliation Rate: Percentage of non-human identities tied to an owner and workload.
High-Risk Privilege Exposure: Agents with payment, code-signing or data-deletion rights.
Rotation Half-Life: Time to rotate keys or tokens.
Toxic Combinations: Cross-system conflicts open beyond policy.
Remediation Velocity: Median days from detection to verified fix.
Audit Lead Time: Time to produce defensible evidence packs.

Each of these metrics has a cost, a risk curve and an accountable owner.

Procure With Identity Clauses

If vendors ship AI agents or automation features, insist on contractual controls: rotation APIs, tamper-evident logs and the ability to export identity data to your graph. Require compatibility with your identity and access governance and management system so that approvals and revocations occur when and where auditors expect them. In cloud agreements, treat machine identities like regulated data: who can see them, how they’re stored and how breaches are disclosed.

Align Insurance And Capital Costs

Cyber insurance underwriters increasingly ask for evidence of identity hygiene. Being able to export time-stamped lineage—from policy to identity to action to remediation—reduces uncertainty and premium pressure.

Just as importantly, a trustworthy identity model lowers the implicit cost of capital for automation projects. If you can test access changes safely, finance can green-light AI initiatives faster and avoid contingency buffers that dilute return on investment. Better data lowers premiums, accelerates approvals and protects enterprise value today.

Talk To The Board In Business Terms

Board members don’t want to hear about tokens and scopes; they want to understand materiality. Show how many agents can move money, alter code or change the ledger today, how quickly you can reduce that number and how evidence will be produced. Frame identity as operational resilience and regulatory defense.

Planning Activities CFOs Can Sponsor

Baseline And Ownership: Begin with a read-only ingestion for HR, directories, cloud, ERP and key SaaS systems. Build the first unified access map and assign ownership for every identity.
Risk Reduction Priorities: Identify and remediate top toxic combinations, rotate high-risk credentials and establish life cycle governance for joiners, movers and leavers.
Non-Human Oversight: Design a process for reviewing and certifying non-human identities across finance, ensuring all revokes are traceable.
Governance Framework: Define access KPIs and reporting cadence. Compile and publish reporting packs, and report progress to the audit committee or board.

Four Steps To Achieve 'Good'

Step one: Assign ownership for every non-human identity. Define purpose, rotation policy and reduce high-risk privileges to essentials.

Step two: Identify toxic combinations, time-box exceptions and make evidence exportable on demand.

Step three: Automate access reviews and simulate access changes before implementation.

Step four: Deliver faster outcomes, reduce incidents and achieve cleaner audits.

The CFO’s Leverage

Boards are signing off on the use of AI, regulators are watching and insurers are pricing uncertainty. The control that reconciles all three is identity. If agents can modify ledgers, vendors or code without clear ownership and least privilege, we’ve introduced material risk.

Finance leaders don’t need to be IAM experts to lead this shift. We should insist on daily visibility, life cycle discipline and provable controls for the agents that power our business. Treat machine identity like payroll: accurate, reconciled and governed.

The companies that learn to scale automation with trustworthy identity data will ship faster, withstand shocks and compound value. Those that don’t will grow risk as quickly as they grow their bots.

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CMO, Meet Your New Workforce: Governing Human And Non-Human Identity - Gathid

Gathid — Thu, 08 Oct 2026 22:26:11 GMT

The most transformative change in marketing isn’t a new channel or a shiny tool; it’s a new workforce. Agentic AI—bots, services and automations that can plan, decide and execute—now works alongside people across content, media, commerce and customer operations. Gartner predicts that by the end of 2026, 40% of enterprise apps will feature task-specific AI agents.

This shift creates extraordinary opportunity, and it also imposes responsibility: CMOs must govern identity and access with the identical rigor we apply to brand voice and financial approvals.

From Co-Pilots To Colleagues

Agentic AI is not a helper that waits for prompts. Agents can publish creative variants, adjust bids, modify product feeds, open tickets and update customer profiles. They can make thousands of micro-decisions faster than any human team member. Without provenance and arbitration, those micro-decisions become invisible and unaccountable.

Without strong identity, scope and provenance, speed becomes fragility. With it, CMOs can compress cycle time, reduce errors and scale personalization with confidence. Governance must be embedded before you scale.

Identity Is Now A Brand Control

Who or what can speak in your name, and to whom, defines brand experience and risk. Nearly 90% of breaches involve compromised credentials, and that includes non-human identities.

Identity and access governance isn’t just “MFA for marketing tools.” It’s the control plane for permissions, consent and accountability.

If an agent can push content to millions, approve a discount or alter a data model, its entitlements are brand controls. Treat them as such: minimum necessary scope, clear owners and time-boxed privileges, with evidence on demand.

Build The Foundation: A Knowledge Graph And An Identity Digital Twin

Most marketing stacks are a patchwork. Rights management lives in a digital asset management hub, consent in a content marketing platform, identity in directories and entitlements inside apps.

A knowledge graph links audiences, claims, assets, channels and approvals. An identity digital twin models people and non-human actors, systems they touch and what they can do. The model is rebuilt daily, surfacing access drift before it compounds into risk.

Together, they let you answer the questions that matter: Who created this asset? Under what consent? Who can change it? Who has permission to push it live? What happens if we revoke a permission set, swap a role or retire an agent?

Guardrails That Scale Creativity

Great marketing requires creativity at speed. Governance should enable, not smother, that speed.

Design role archetypes (creator, publisher, analyst, agent operator) with least-privilege scopes. Apply joiner-mover-leaver to human and non-human identities: owner, sponsor, purpose, end date. Define toxic combinations such as “publish + approve brand claims” that concentrates risk. Add compensating controls where separation isn’t feasible. Require provenance for every asset and dataset so disputes become traceable facts, not opinions.

A New Operating Model For Creative Systems

Rework your team topology around creative systems, not only channels. Pair brand, data, engineering and legal in a standing pod that defines prompts, policies and review rituals.

Give product managers for content and data the mandate to orchestrate agents, not just buy tools. Instrument the system so leaders see flow from brief to audience to asset to outcome, with bottlenecks and risks visible.

This isn’t just tooling, but a work redesign for humans and agents operating in tandem.

Procure Agents Like You Buy Media

You will soon buy agents from vendors the way you buy inventory from publishers. Insist on identity clauses in contracts: per-tenant secrets, rotation APIs, tamper-evident logs, consent inheritance and export of identity data to your governance layer. Price against business outcomes, not token usage. Demand explainability for regulated use cases and a hard off switch you control. If a partner can’t meet those standards, you’ll inherit unpriced risk.

Metrics That Earn The Board’s Trust

Boards don’t want a demo. They want proof. Report governance metrics that tie identity to performance, such as consent coverage by audience, provenance rate for published assets, agent-to-owner reconciliation, revoke velocity, exception half-life, and time-to-evidence for claims and approvals. Add efficiency metrics to show that governance accelerates output: cycle time per asset, reuse rate and first-time-right rate.

Finally, include a risk lens. The number of agents with publishing rights and the share operating with least-privilege scopes should trend down over time.

Privacy As A Growth Strategy

Personalization only works when it is trusted. Seventy-four percent of consumers say they won’t buy from brands that lose their trust on data. Treat consent as a product surface, not a legal afterthought. Make preferences transparent, honor them everywhere agents act, and ensure models never learn from data that wasn’t granted.

The payoff is measurable: higher opt-in rates, lower suppression and fewer brand-damaging reversals. Build creative that assumes consent can change and degrades gracefully.

Design For Resilience, Not Perfection

Incidents will happen. There will be mis-scoped permissions, rogue automations or human error. The goal isn’t zero defects, but fast, accountable recovery.

With an identity digital twin, you can trace who or what acted, roll back quickly and produce auditable evidence. With a knowledge graph, you can correct claims and content across every surface consistently, without days of manual investigation.

The Leadership Moment

Half of U.S. employees already use AI tools at work without telling managers. The workforce has changed whether you’re ready or not. This is the moment for CMOs to earn a durable seat at the transformation table. By governing identity with the discipline of finance and the empathy of brand, we can scale AI responsibly, accelerate growth and deepen trust. The alternative is to let the fastest-growing part of our workforce operate without the controls we expect from people. That’s not acceptable for our customers, our teams or our brands.

Set the guardrails. Measure what matters. The work will be artful, accountable, resilient and worthy of the brand you steward. Governance isn’t bureaucracy. It’s how you turn acceleration into trust.

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Authority Drift Is Quietly Destroying Your Role Model - Gathid

Gathid — Thu, 08 Oct 2026 22:26:10 GMT

Most role models don’t fail overnight. They degrade. Slowly. Quietly. Almost invisibly.

What begins as a clean, well-structured design (aligned to business functions and governance policies), gradually becomes something else entirely. More complex. Less predictable. Harder to trust.

This is not a failure of design. It’s a failure to account for how authority evolves.

The Assumption Behind Role Models

Role-based access control is built on a simple idea: define the right roles, and access will remain structured, scalable and secure. At the point of creation, this often holds true. Roles are carefully designed. Permissions are mapped. Governance is applied.

The problem is, that model assumes something that rarely exists in practice: that the environment will stay still. It won’t.

How Authority Actually Evolves

Inside a real enterprise, authority is not static. It accumulates and changes over time—through entirely legitimate activity:

Exceptions granted to meet immediate needs
New systems integrated into the environment
Mergers and acquisitions introducing overlapping roles and structures
Automation and service identities extending access beyond human users
Incremental changes that are never fully rolled back

Each change makes sense in isolation. But collectively, they reshape how authority exists across the organization. This is authority drift—the gradual divergence between intended role design and actual authority.

Why Drift Goes Unnoticed

Authority drift doesn’t trigger alarms. It doesn’t appear as a single event or a clear violation. It builds over time, across systems and teams. Most identity systems are not designed to detect it.

Instead, they track things like provisioning. They enforce policy, and they support access reviews.

In addition, they operate on snapshots that capture what was granted, and what exists now, rather not on the evolving structure of authority. As a result, drift accumulates quietly, beneath the surface of governance processes that appear to be working.

The Consequences of a Drifting Model

Over time, the impact of this situation becomes visible:

Roles that once made sense no longer reflect how people actually work.
Exceptions become the norm rather than the exception.
Access reviews become harder to complete with confidence.
IAM programs slow down because the role model is no longer trusted.

Most importantly of all, risk increases. This is because authority is no longer aligned to intent. It has spread, combined and concentrated in ways the original design never anticipated.

The Illusion of Control

From the outside, everything can still look under control. Roles exist. Policies are defined. Reviews are completed. However, the organization is no longer operating on the model it believes it has. Instead, it is operating on the model that has emerged over time.

And those are not the same thing.

This is the gap between intent and reality—between roles as designed and authority as it actually exists.

Why Rebuilding Isn’t Enough

When this gap becomes too large, organizations often respond by rebuilding the role model. New workshops. New definitions. New structures. For a moment, things improve. Then drift begins again. This is because the underlying issue hasn’t been addressed: the organization still lacks visibility into how authority evolves.

Without that, every role model is a temporary state; accurate only at the moment it is defined.

Detecting Drift Before It Becomes Risk

To manage authority drift, organizations need to shift from static design to continuous understanding. That means being able to see:

How authority is changing over time
Where it is concentrating
Which roles are diverging from their intended scope
How new systems and integrations are altering the structure

This requires more than reviewing access. It requires modelling authority as a connected structure across identities, roles, systems and credentials. Only then can drift be detected as it happens, not after it has already created risk.

From Static Roles to Living Models

A role model should not be treated as a fixed design. It should be treated as a living structure that evolves alongside the organization. When authority is understood continuously, teams can:

Identify divergence early
Adjust roles before they become misaligned
Reduce the accumulation of exceptions
Maintain alignment between governance and reality

This transforms role management from periodic correction to ongoing control.

Don’t Let the Model Decay

No role model stays accurate on its own. Left unmanaged, it will drift, pulled by the natural evolution of the enterprise.

The organizations that maintain control are not the ones that design the best roles once. They are the ones that continuously understand how authority actually exists—and adjust accordingly. Because the real risk isn’t that your role model was wrong. It’s that it quietly stopped being true.

Compare approved access roles vs actual account access - Gathid

Gathid — Thu, 08 Oct 2026 22:26:09 GMT

In the realm of Governance, Risk, and Compliance (GRC), determining “who should have access to what” based on job titles can often resemble untangling a complex web. Whether you are embarking on your GRC journey or delving deep into the complexities of Identity and Access Management, it’s evident that effectively managing this aspect is no simple task. GRC processes and policies serve as the unheralded champions that ensure our organizations operate seamlessly.

GRC‘s main objective is to ensure that individuals starting a new role or transitioning within the organization are equipped with the appropriate level of access needed to perform their duties efficiently. Equally significant is the offboarding process for departing employees, which ensures that they no longer retain access to sensitive systems and data.

The Complex Landscape of User Access Management

In today’s dynamic business environment, changes occur frequently. HR and procurement departments often introduce new position titles, while the Information Technology (IT) team continuously manages an expanding array of systems across hybrid and multi-cloud environments. Moreover, the requirements for access and assets essential for daily operations can change rapidly. As a result, the role mappings that are diligently established may become obsolete almost immediately after completion – and long before automation can be implemented.

Identify & Review Unauthorized Access

The Gathid platform applies a unique approach due to its patented directed graph technology, reading and modeling your identity data daily while ensuring it aligns with established policies and processes. Right from the beginning, organizations can easily utilize Gathid without needing to build a host of complex integrations; getting started is as easy as uploading your system, service, or application identity data via API, CSV or SFTP in order to determine the correlation between position titles and access rights of individuals.

With Gathid, those responsible for identity and access governance can proactively fine-tune their organization’s GRC controls and processes with pinpoint accuracy, thanks to the source-of-truth context it provides daily.

Gathid doesn’t just model your data on a daily basis – it automatically identifies any inconsistencies and brings them to your attention. It allows you to systematically create a daily report that acts as a system of record that highlights the roles or accounts that deviate from your master records. It’s akin to having a reliable compass guiding you through the complicated maze of user identity. Consider a large financial institution with multiple branches, each with staff with differing levels of access – potentially across multiple branches. This model becomes incredibly complex in short order, moving an accurate access model requirement from a “nice to have” to a “must have” for reducing associated risks.

For many organizations, Gathid is a “secret weapon” for regaining control and visibility over the complexity of access management and governance. It enables you to compare officially approved roles with actual access, and it does so each day. It allows organizations to streamline, secure, and simplify their governance, risk, and compliance activities in relation to identity and access – saving you time, money, and effort.

Expert Tips To Identify And Act On Data Overload - Gathid

Gathid — Thu, 08 Oct 2026 22:26:08 GMT

Data may be “the new oil,” but as human experience has shown time and again, there can be too much of a good thing. The essential insights and information quality data provides can be diluted or even distorted when a company is drowning in disorganized, irrelevant or duplicated data.

From better decisions to lower operational costs, there are compelling reasons for every organization to keep a close watch on the volume and quality of data it collects and stores. Below, members of Forbes Technology Council share their expert tips to help company leaders identify—and, more importantly, address—data overload.

“When data access becomes unwieldy and error-prone, indicating overcollection, consider integrating advanced identity and access management solutions. These tools employ AI and digital twins to analyze data usage patterns and streamline access controls so that only relevant data is actively managed and accessible to authorized users. This enhances security by minimizing unnecessary data exposure.” – Craig Davies, Gathid

1. Implement A ‘Data Hygiene’ Strategy

It’s clear a company is overwhelmed by data when decision making slows down because teams spend more time sifting through information than deriving insights. To correct this, leaders should implement a “data hygiene” strategy: Prioritize key metrics aligned with business goals, regularly audit data for relevance and eliminate redundant or low-value data. This keeps your focus sharp and your processes efficient. – Andres Zunino, ZirconTech

2. Consider A Centralized Data Team

All data is helpful and valuable, but you know you’re having a hard time managing data when you can’t make sense of it. This could be due to a combination of disparate tools and teams that own different parts of it. We talk a lot about a centralized data lake, but little about a centralized data team that owns all the required pieces. – Rajaram Srinivasan, Unbound Security

3. Avoid Superfluous Metrics

To paraphrase Goodhart’s law, “When a metric becomes a target, it stops being a metric.” A company that collects too much data falls into the trap of defining superfluous metrics and measures, with teams spending time reviewing them rather than focusing on transformative impact. This is when you know you’re trying to manage too much data. – Harini Gopalakrishnan, Snowflake

4. Enforce Data Minimization

A sign of excessive data collection is when a company gathers data without having a rationale for its collection or use. To address this, a company can enforce data minimization, which ensures data is only collected for a specific purpose. Conduct regular brainstorming sessions to assess whether the data elements being collected are still relevant or if unneeded data can be deleted. – Aparna Achanta, IBM

5. Make Sure The Value Of Collected Data Is Understood

When the value derived from data is significantly smaller than the resources, both human and technological, spent on its collection and management, it raises questions. If the value of the collected data is not understood, it puts the entire data program at risk of budget cuts. – Michael Nirschl, Morgan Stanley

6. Connect Data Elements To Meaningful Analytics

A quick test of whether you are managing too much data (which is different from collecting too much) is to look at the managed dataset and see if you can legitimately connect those data elements to meaningful analytics that are in use by the organization’s operations, management and governance teams. If there isn’t a clear connection, you are likely managing way too much data—potentially 10 times too much data. – Terrance Berland, Unicorn & Lion LLC

7. Prioritize Metrics Aligned With Business Goals

A clear sign a company is overwhelmed by data is when decision making slows due to analysis paralysis, with teams spending excessive time sorting through data instead of acting. Leaders can correct this by prioritizing key metrics aligned with business goals, simplifying data streams and fostering a culture focused on actionable insights over sheer data volume. – Marius Ivanauskas, Zurich Insurance

8. Watch For Signs Of ‘Data Fatigue Syndrome’

You know there’s a problem when “data fatigue syndrome” sets in—when staff become numb and unresponsive to the constant barrage of metrics, reports and analytics. Some of the signs? Meetings are eerily quiet when data is presented, with few questions or engagement. Data-driven initiatives consistently underperform despite robust analytics. Staff shows a near-allergic reaction to numbers, glazing over at the mention of KPIs. – Nick Newsom, Ytel Communications

9. Take A Value-Over-Volume Approach

A company that struggles to extract actionable insights from data may be focused on data volume rather than its quality or relevance. Instead, prioritize high-value data that directly impacts business objectives and customer outcomes. A value-over-volume approach enables faster, more informed decisions; reduces the burden of managing excessive and redundant data; and drives meaningful outcomes. – Michael Meucci, Arcadia

10. Set Clear Retention Rules, Tag Information And Automate Cleanup

If your company is overwhelmed by data, you’ll notice “storage inefficiency”: Too much irrelevant data piles up, making it hard to find what’s important. To fix this, focus on collecting only valuable data, set clear retention rules, categorize and tag information for easy access, and automate data cleanup to keep things efficient and manageable. – Phil Portman, Textdrip

11. Integrate Advanced Identity And Access Management

When data access becomes unwieldy and error-prone, indicating overcollection, consider integrating advanced identity and access management solutions. These tools employ AI and digital twins to analyze data usage patterns and streamline access controls so that only relevant data is actively managed and accessible to authorized users. This enhances security by minimizing unnecessary data exposure. – Craig Davies, Gathid

12. Identify Priority Data

The question is not how much is too much data, but what data is important to facilitate a business’s existence and growth, and how does that data align with corporate and customer KPIs or compliance requirements? Once companies identify their priority data, they can make data-driven decisions for data storage requirements. -David Bennett, Object First

13. Conduct An Audit And Revisit Your Retention Policy

One sign a company is collecting and trying to manage too much data is when its storage costs go high while its value remains low. To address the issue, conduct a data audit to make sure you’re going for quality, not quantity. Plus, revisit your data retention policy and potentially revise it to further optimize data management and storage costs. – Yuriy Gnatyuk, Kindgeek

14. Optimize AI Deployments

Customizing and fine-tuning AI models for specialized tasks is a data-intensive exercise. Gartner notes that, in 2023, companies deploying AI spent between $300,000 and $2.9 million just on inference, grounding and data integration. If companies are not optimizing their AI deployments for a careful balance between accuracy, speed and cost, their data center budgets will quickly spiral out of control. – Vivek Jetley, EXL

15. Launch A ‘90-Day Data Challenge’

If your database backup windows are creeping from hours into days while query response times keep slowing down, you’re hoarding too much data. Leaders should launch a “90-day data challenge”—temporarily archive any dataset not accessed in the past 90 days, then only restore what teams actively request. After 30 days, permanently delete unrequested archives. – Balaji Dhamodharan, NXP Semiconductors

16. Categorize Collected Data

If a company has one-size-fits-all data retention policies, that’s a clear sign it’s collecting and trying to manage too much data. I suggest clearly categorizing each type of data you’re collecting and defining a retention period for each type. Some data can be deleted in two weeks, while some needs to be kept around for years, and your policy should reflect that. – Deepak Bhaskaran, Cisco Systems Inc.

17. Automate Data Collection, Analysis And Management

Eliminate unnecessary manual processes by automating data collection, analysis and management. For instance, banks and financial services firms by nature analyze massive amounts of data. Onboarding and transactions can be slow and cumbersome, which can lead to a poor customer experience. Automation improves the quality and speed of digital client journeys and enhances overall security and compliance. – Alex Ford, Encompass Corporation

18. Leverage Data Management Technologies

One sign a company is collecting too much data is a frequent need to increase storage capacity. It is very easy for IT staff to just keep buying more storage, but there are more sophisticated methods available—for example, technologies like thin provisioning, deduplication and data thinning (automatically deleting data that is not needed). There is so much data being stored that will never be used again. – Bruce Kornfeld, StorMagic

19. Conduct A Full Data Analysis

Keep an eye out for data sprawl across different systems—databases, cloud file services and so on—without data classification. Data becomes hard to secure, leading to duplications or, even worse, people (and AI training models) processing outdated documents. The answer is a full data analysis. Build data governance policies and utilize advanced data management tools to streamline storage and maintain data integrity. – Carl D’Halluin, Datadobi

20. Simulate A Data Breach

A simulated data breach often shows that a company is collecting too much data. If the results come in and everyone wonders where certain data came from and how it is stored, it’s time to dig deeper into your collection and storage practices. The first step in the process should be listing all the data silos within the company to gain an overview of what’s there. – Kevin Korte, Univention

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20 Ways To Combat Misinformation Amid More And More Synthetic Media - Gathid

Gathid — Thu, 08 Oct 2026 22:26:07 GMT

As today’s technology and political divisions continue to evolve, “fake news” and AI-generated deepfakes continue to blur the lines between fact and fiction. Companies face growing pressure to take a stand on truth and transparency, especially when their own brand is being misrepresented. However, determining how proactive to be—and when to step back—can be a delicate balancing act.

To help, Forbes Communications Council members explain how companies can responsibly engage in the fight against misinformation while protecting credibility, trust and brand integrity.

“Brands can’t stay silent in a misinformation economy, yet they also shouldn’t act as arbiters of truth. Their role is to be a beacon of verified authenticity. That means prioritizing identity-verified content, transparent sourcing and auditability across every channel. The goal isn’t to out-shout misinformation. It is to earn trust through proof, precision and consistency.” – Hope Frank, Gathid

1. Educate Your Consumers And Establish A Trust Center

Brand impersonation and misinformation have become some of the most under-recognized business risks today. While cybersecurity teams can take down look-alike domains, marketing and comms pros can play an active role, too. Educate your customers on how you communicate. Establish a trust center. Align marketing, legal and cybersecurity teams, and measure exposure, not just incidents. – Chris McKie, Embed Security

2. Fact-Check Data And Clarify AI Use

In B2B organizations like ours, trust drives deals. Brands must model transparency by fact-checking data, clarifying AI use and elevating credible voices. When buying cycles are long and stakes are high, authenticity isn’t just ethics—it’s revenue protection. – Anna Eliot, pharosIQ

3. Build Trust Through Relentless Consistency

Trust is the only real defense against misinformation. In a crisis, you won’t have the resources to wage hand-to-hand combat with every lie. Trust is built through relentless consistency between what you say and what you do. That consistent alignment creates a defensive moat when misinformation inevitably targets you. – Bradley Akubuiro, Bully Pulpit Interactive

4. Shape Your Preferred Brand Narrative Through Owned Content

Brands must take an active role in shaping their own narratives. By telling your story consistently and ensuring owned content is optimized for discovery across search and AI chatbots, you give audiences direct access to your preferred brand narrative. This strengthens consumer trust and helps set the tone for third-party narratives, creating alignment across your brand’s constellation of assets. – Shannon Reedy, Terakeet

5. Publish Journalistic Content That Builds Trust

Part of your content marketing program can include journalism that combats misinformation. This valuable content should acquire leads and build trust. You’re only too proactive if you assume you have everything figured out. Remind readers that you’re open to their feedback and willing to update stories as new info becomes available. – Joseph Rauch, Joseph Rauch, LLC

6. Have Your C-Suite Deliver The Right Message At The Right Time

Silence creates stagnation. Proactive, consistent communication ensures accurate information sharing, which safeguards reputation. The C-suite needs to be out front with the right message at the right time. A sustained practice of being clear and authentic carries brands through more chaotic times, even when facts change or appear uncertain. – Rachel Kule, Pursuit PR

7. Proactively Vet Your Own Content And Lead With Clarity

Proactive doesn’t mean reactive. It means responsible. Your brand should be a lighthouse, not a loudspeaker. Be proactive about vetting your own content, from claims to visuals to sources. Train spokespeople and AI users internally to flag hallucinations, misattributions or bias. Lead with clarity, citations and real-world context, especially in complex B2B spaces where the truth is often nuanced. – Colby Proffitt, Carbyne

8. Shift From A Content Creator To A Trust Infrastructure

Brands must move from content creators to trust infrastructures. That could mean blockchain-verifiable messaging, AI watermarking or even partnering with journalists and fact-checkers. If we want attention, we must earn credibility, algorithmically and emotionally. – Jorge Lukowski, NEORIS

9. Ensure Every Message Is Factual, Consistent And Transparent

Protect credibility through clarity. Verify information before sharing, cite reliable sources and correct mistakes quickly. Trust grows when every message is factual, consistent and transparent. The role of a brand is not to react to every rumor but to communicate honestly, educate its audience and stay steady when uncertainty spreads. – Sarah Chambers, SC Strategic Communications

10. Anchor Your Narrative In Verifiable Facts

In an era of fear, uncertainty and doubt (FUD), our role as communication professionals is to consistently anchor the narrative in verifiable facts. “Too proactive” is leaving your center to fight on the periphery, validating the noise. A brand with true gravity pulls the conversation back to reality, letting FUD collapse on its own. – Reyne Quackenbush, Thoughtworks

11. Share Your Opinions And Don't Sway From Them

Brands need to be conscious of what is said about them in the market so they can help control the narrative. Interject into the conversation, make your opinions and stances clear and don’t sway from them. If a brand stays authentic and true to its beliefs, consumers will know what’s real and what’s fake. – Joe Ariganello, Veracode

12. Cite Your Sources And Leverage Real Professional Endorsements

Connecting content to source is one key way to help fight misinformation. Brands can borrow from the academic playbook and cite sources, directly link to verified content and data, and leverage true professional endorsements from real humans. – Barnaby Pung, Merit Network

13. Be Transparent About Your AI Usage

Brands should be transparent about when AI is used in their content or products. Labeling AI-generated material builds trust and sets ethical standards. In an era of misinformation, honesty about how content is created is just as important as the message itself—it reinforces credibility and accountability. – Cody Gillund, Grounded Growth Studio

14. Be A Beacon Of Verified Authenticity

Brands can’t stay silent in a misinformation economy, yet they also shouldn’t act as arbiters of truth. Their role is to be a beacon of verified authenticity. That means prioritizing identity-verified content, transparent sourcing and auditability across every channel. The goal isn’t to out-shout misinformation. It is to earn trust through proof, precision and consistency. – Hope Frank, Gathid | Gathered Identities

15. Build A Strong Record Of Reliability

In the deepfake era, credibility is currency. Brands should anchor their communication in traceable truth—showing sources, clarifying AI use and owning corrections. The goal isn’t to fight every falsehood, but to build a record of reliability so strong that misinformation can’t compete with your consistency. – Katie Jewett, UPRAISE Marketing + Public Relations

16. Create A Measurable Process For Addressing Misinformation

If you aren’t proactive at this point, you’re unprepared to handle misinformation. Create a process to address misinformation that provides transparency and clarity. Treat your brand’s credibility as a KPI. Measure it. – Jennifer Best, AmICredible

17. Invest In Content Verification Technology And Processes

In an age of misinformation, brands must take a proactive role in safeguarding truth. This includes investing in content verification technology and processes, building rapid response and correction protocols and educating audiences before falsehoods gain traction. Proactivity must be measured, as overreach can erode trust. Credibility comes from consistent, transparent and principled action. – Rob Robinson, HaystackID

18. Correct Errors Quickly And Don't Amplify Rumors

Brands should treat truth as a core value and show their work. They should publish sources and keep a rapid fact-check lane with legal and comms. They should correct errors quickly, never amplify rumors and partner with trusted third parties when needed. Be proactive, not performative. – Heather Stickler, Tidal Basin Group

19. Combat Misinformation That Directly Affects You

Brands should combat misinformation that directly affects them and support a broader information infrastructure (fact-checking, media literacy) without overreaching. Key actions include transparent communication, rapid response to false claims, responsible ad placement and verified channels. The risk is becoming truth arbiters beyond their expertise or weaponizing “misinformation” against legitimate criticism. – Anshuman Dutta, Cognizant

20. Double Down On Original Pieces And Real Moments

See opportunity in the deepfake fog. While others fight rumors, double down on what can’t be faked at scale: original set pieces and real, live moments. Host unscripted demos, open-studio days and Q&As. Publish one-take, behind-the-scenes cuts with timestamps and receipts. Don’t claim you’re real—prove it. When others zig into synthetic polish, you zag into undeniable reality. – Sanel Mezbur, Arkenstone

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15 Expert Tips For Companies Embracing Digital Hiring Tools - Gathid

Gathid — Thu, 08 Oct 2026 22:26:07 GMT

For more and more companies and professionals, filling or landing a job is primarily a digital process. There are many online job sites, and organizations often opt to maintain an updated list of job openings on their websites. And as more businesses embrace remote and global workforces, in-person résumé submissions and interviews are increasingly a relic of the past.

“Knowing who has access to what data and systems across the organization should be priority No. 1. Poor user access and identity governance processes create huge risks, from access creep and identity debt to toxic role combinations. Auditing user privileges, implementing least-privileged access and getting a handle on employee onboarding and offboarding processes will ensure a successful journey.” – Craig Davies, Gathid

Today’s job listings may reach interested applicants from around the globe, and a company may receive hundreds of résumés for a single position. Having a human review every résumé received is an increasingly difficult, if not impossible, prospect. But by leveraging digital tools and platforms, companies can streamline recruitment, improve the applicant experience and gain a competitive edge in the race for top talent. Below, 15 members of Forbes Technology Council share their expert tips for companies seeking to leverage digital tools to improve and support hiring processes.

1. Seek To Augment Human Insights

I would suggest prioritizing technologies that augment human insights, not replace them. For example, use artificial intelligence for initial résumé screening to efficiently identify top candidates, which will give HR more time to assess their soft skills and cultural fit. This method enhances both efficiency and the quality of hires. Ensure the adoption of new technology is strategically aligned and includes comprehensive training for the HR staff. – Krishnan Gopi, GEMS Education

2. Carefully Manage User Privileges

Knowing who has access to what data and systems across the organization should be priority No. 1. Poor user access and identity governance processes create huge risks, from access creep and identity debt to toxic role combinations. Auditing user privileges, implementing least-privileged access and getting a handle on employee onboarding and offboarding processes will ensure a successful journey. – Craig Davies, Gathid

3. Select For Scalability And Culture Fit

Start by selecting technology that’s not only scalable and integrates well, but that also aligns with your business needs, company culture and mission. Ensure the digital tools enhance both candidate and team experiences, and continually evaluate their effectiveness to keep your hiring process agile and aligned with your goals. – Rachel Lyubovitzky, Setuply, Inc.

4. Maintain An Emphasis On People Skills

High-performing digital transformation specialists need to have not only analytical and technology skills, but also people skills. The biggest barrier to transformation is not technology; it’s change management itself. Those with an empathic approach to change will deliver the most lasting results. – James Duez, Rainbird Technologies

5. Prioritize The UX

One piece of advice for companies embarking on a digital transformation journey in their hiring processes is to prioritize the user experience. Ensure that the digital tools and platforms used in the hiring process are intuitive, accessible and user-friendly to provide a positive experience for candidates and hiring managers. – Pavel Kovalenko, Langate Software

6. Ensure The Tools Meet The Needs Of All Workers

Adopt digital hiring tools that meet the needs of all workers, including front-line teams, which may see significant shortages in terms of available talent. Personalize the candidate experience to demonstrate your employee experience and preserve your core company values. This strategy can differentiate you as an employer of choice and help you win new talent while strengthening your employer brand. – Jeff Moses, WorkForce Software

7. Monitor Key Recruitment Metrics

Utilize data analytics to monitor key recruitment metrics, such as time to hire, cost per hire and candidate satisfaction. This approach enables you to identify hiring process bottlenecks and refine recruitment strategies for improved efficiency and effectiveness. Data is transparent and never lies. – Phil Portman, Textdrip

8. Invest In An Effective ATS

An effective application tracking system can automate routine tasks such as sorting résumés and scheduling interviews, which not only speeds up the recruitment process, but also helps reduce human bias, ensuring a more objective and inclusive hiring approach. Additionally, it’s important to select an ATS that provides robust analytics capabilities. – Roman Reznikov, Intellias

9. Reverse-Engineer Your Hiring Process

Reverse-engineer the hiring process and assess where the infusion of cutting-edge technology can make it better. For example, recruiters spend countless hours simply scheduling interviews. If you can harness technology and digital tools to make that process easier and more efficient for your recruiting team, it can have a massive positive impact on the entire hiring process and experience. – Gleb Polyakov, Nylas

10. Take A Holistic Approach

Do not take a siloed approach. Take a holistic approach by considering the experiences of all the stakeholders involved, including the candidates, recruiters, hiring managers and management team. The implementation can be undertaken with a phased, agile approach once you have a complete view of the digital transformation of HR processes. – Selva Pandian, DemandBlue

11. Start Mapping The Data Captured At All Stages Of Hiring

After a decade of carrying out digital transformations of various enterprises’ hiring processes, I believe the best option is to start mapping the data being captured across all stages of hiring to see where digital transformation can add the most value. Do not start with the technology first. Instead, first analyze the situation in terms of people and processes. Then, you can consider technology augmentation as a part of your newly designed “future state.” – Amal PS, Omind

12. Work Out A Gradual Process

“Complete revolution” and “disruption” are buzzwords that have tempted many organizations. However, betting on a well-planned and managed digital transformation usually provides better returns, especially in areas such as hiring, which involves handling sensitive personal data. Gradual moves toward automation will make processes more efficient, while fast and radical changes may create unnecessary risks. – Julius Černiauskas, Oxylabs

13. Clarify Your Desired Outcome

Start with a clear vision of your desired outcome and select technology that enhances, not complicates, the candidate experience. Embrace tools that automate routine tasks, but prioritize human interaction for critical touchpoints. This balanced approach ensures efficiency while maintaining the personal engagement that attracts top talent. – Miguel Llorca, Torrent Group

14. Thoroughly Train Your HR Team On Data-Driven Decision-Making

Start by clearly defining your goals and identifying the specific problems you want to solve with digital tools. Invest in user-friendly platforms that enhance the candidate experience and automate routine tasks. Also, ensure thorough training for your HR team to leverage these technologies effectively, focusing on data-driven decision-making to improve hiring quality and efficiency. – Saif Sultan, Volos Portfolio Solutions, Inc.

15. Consider Your Product Options Carefully

Consider your hiring tech stack carefully. Some products lock you into their ecosystems but work seamlessly, while others provide a lot of integration options but are just a point solution. Depending on your organization’s appetite for managing new implementations, the tech stack you choose will have a big effect. – Mang-Git Ng, Anvil

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20 Emerging Tech Tools Reducing Digital And Physical Job Risks - Gathid

Gathid — Thu, 08 Oct 2026 22:25:55 GMT

From factory floors to remote digital workspaces, worker safety is being reshaped by technology. Advances in artificial intelligence, wearables, automation and immersive tools aren’t just reducing accidents and cybersecurity incidents. They’re also enabling companies to predict and prevent them, shifting from reactive measures to proactive strategies that more effectively protect employees.

Workplace risks are no longer confined to heavy machinery or hazardous materials. In an era where digital threats are as disruptive as physical hazards, safeguarding workers means protecting both health and data. Below, members of Forbes Technology Council highlight the tools and advancements they see as most significant in improving worker safety.

“Leading-edge identity governance technology, like digital twins, is transforming worker safety by giving organizations a real-time, contextual view of every identity and access relationship across IT, OT and physical systems. This visibility helps detect unsafe access paths or privilege overlaps before they cause harm, protecting both digital and physical environments.” – Craig Davies, Gathid

1. Smart Wearable Sensors

I think wearable sensors with real-time AI analysis will be one of the most significant advances for worker safety. These smart wearables can monitor multiple safety indicators simultaneously, including environmental hazards, physiological measurements, movement patterns and proximity alerts. What makes this technology particularly powerful is that the AI component can predict accidents before they happen. – John Akkara, Smoothstack

2. Zero-Trust Security Frameworks

One recent advancement that has had an impact is zero-trust security frameworks combined with passwordless authentication. In an age of hybrid work, cloud services and sophisticated phishing attacks, it decreases the issues associated with perimeter-based security. It shifts the approach so every user, device and request must be authenticated and authorized continuously, regardless of location. – Len Covello, Engage People Inc.

3. Digital Environmental Safety Tools

Cyber and digital environmental safety tools protect employees from online threats, protecting both people and data. Tools such as AI-powered email filters, phishing simulations and password managers reduce human error risks and safeguard employees. – Pooja Sathe, Lenovo

4. AI-Powered Computer Vision

AI-powered computer vision with edge processing is transforming worker safety by detecting hazards—like missing personal protective equipment, unsafe machinery proximity or dangerous postures—in real time. Instant alerts to workers and supervisors turn safety from reactive to proactive, reducing accidents before they happen—even in low-connectivity environments like construction, mining and logistics. – Suri Nuthalapati, Cloudera

5. AI Dashboards For Fatigue And Hazard Detection

Worker safety is shifting from checklists to dashboards. By fusing data from wearables, sensors and shift patterns, AI detects fatigue and hazards before incidents occur. One plant I’m aware of saw 48% fewer near misses and 65% faster responses. This transforms safety from reactive compliance to proactive prevention. – Farrukh Mahboob, PackageX

6. Vibe Coding For Human-State Awareness

“Vibe coding,” where developers work in an environment that blends real-time feedback, immersive focus tools and adaptive cues, could meaningfully improve worker safety. It could reduce fatigue and human errors by detecting burnout, enhancing response readiness and embedding these adaptive cues into daily workflows. Essentially, it could help monitor real-time human-state awareness for good. – Abhi Shimpi

7. Digital Twins

The advancement of digital twins has immense potential to improve worker safety. By creating a virtual replica of a physical environment, teams can simulate dangerous scenarios and test safety protocols without putting anyone at risk. This technology allows for a proactive approach, echoing the sentiment of the quote, “The best way to predict the future is to create it.” – Uttam Kumar, American Eagle Outfitters

8. Smartwatches

Not only can smartwatches improve cybersecurity by being part of a digital multifactor authentication system that’s tied to biometrics, but they can also alert safety responders about the physical well-being of an individual. At physical jobs, a smartwatch can ping if a worker is not in the right place at the right time, helping ensure both productivity and safety. We will see even more utilization of smart wearable tech in this area. – WaiJe Coler, InfoTracer

9. AI-Enabled Telematics

In high-needs transportation, safety is everything. AI-enabled telematics and wearable tech now monitor driver health, vehicle conditions and surroundings in real time. This proactive approach prevents incidents before they happen, protecting both passengers and drivers. – Gaurav Sharda, Beacon Mobility

10. Browser Isolation

Browser isolation is one advancement I see improving digital worker safety. Instead of relying on users to spot threats, it opens risky content in a secure environment. It’s a quiet shift, but it protects against phishing, malware and data leaks without slowing anyone down. – Nidhi Jain, CloudEagle.ai

11. AR Headsets

Augmented reality headsets are quietly transforming safety training. Instead of learning through manuals, workers can rehearse complex or hazardous tasks in an immersive, risk-free environment mirroring real-world conditions. This boosts retention, builds memory and reduces on-the-job mistakes, making safety less about reacting to incidents and more about preventing them in the first place. – Umesh Kumar Sharma

12. AI-Driven Cognitive Load Management

A powerful new tool for worker safety is AI-driven cognitive load management. This technology analyzes work patterns like meeting density and context switching to identify burnout and mental fatigue. It then provides personalized, real-time nudges to enforce boundaries and optimize focus. This shifts the focus from physical safety to proactive mental well-being and a humane digital work environment. – Mohan Mannava, Texas Health

13. AI-Powered Predictive Risk Assessments

A recent advancement in worker safety is AI-powered predictive analytics for risk assessment. By analyzing data from sensors, wearables and historical incident reports, AI can predict potential safety hazards before they occur. This proactive approach helps prevent accidents by allowing workers to take preventive measures in real time, ultimately improving overall workplace safety. – Tannu Jiwnani, Microsoft

14. Tools That Alert First Responders

Even with sufficient safety equipment and training, emergencies can still occur. The next generation of workforce safety tools focuses on the critical final step: making sure urgent alerts reach the right responders right away, wherever they are. By implementing tools and practices that bridge the gap between incident detection and resolution, organizations can save lives and minimize harm. – Judit Sharon, OnPage Corporation

15. Chat Platforms

The best safety innovation isn’t safety software at all. It’s Discord. Construction crews using gaming chat for instant voice warnings beat any formal safety system. Turns out the same tool that helps teenagers coordinate raids is perfect for yelling, “Crane overhead!” in real time. Who knew safety’s killer app would come from Fortnite players? – Ishaan Agarwal, Square

16. UWB Proximity Tags

Ultra-wideband proximity tags on vests or helmets and on anchors on forklifts measure distance to within inches, triggering graded haptic alerts—or automatically slowing or stopping equipment—when people enter danger zones. Unlike BLE or RFID technologies, UWB’s accuracy reduces false alarms, so crews are more willing to keep the tags on. They’re already cutting “struck by” incidents in warehouses, mining and construction—a practical, high-ROI safety measure. – Pawan Anand, Persistent Systems

17. Voice Assistants

Technologies like voice assistants are improving worker safety by allowing workers to access information, report issues and operate machinery using voice commands. For example, a worker can use a voice-activated device to pull up safety protocols or report a hazard without stopping a manual task, keeping their hands free and their focus on the job. – Harshal Shah

18. Next-Generation Exoskeletons

One advancement is next-generation exoskeletons equipped with neural-interface sensors that detect micro-muscle strain patterns before a worker feels discomfort. They adjust support to prevent injuries during lifting, repetitive motions or awkward postures. By learning individual movement styles, they act as personalized “strength translators” that protect against long-term musculoskeletal damage. – Cristian Randieri, Intellisystem Technologies

19. Warehouse Robots

AI designed to improve workplace efficiency is taking center stage. Amazon, for example, has led by design in its warehouses, demonstrating that AI-powered robots can help reduce workplace accidents by a sizable percentage while working seamlessly alongside their human cohorts for mutual productivity. This is the future of AI and human interaction. – Michael Gargiulo, VPN.com

20. Identity Governance Technology

Leading-edge identity governance technology, like digital twins, is transforming worker safety by giving organizations a real-time, contextual view of every identity and access relationship across IT, OT and physical systems. This visibility helps detect unsafe access paths or privilege overlaps before they cause harm, protecting both digital and physical environments. – Craig Davies, Gathid

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18 Ways Analytics Can Transform Internal Communications - Gathid

Gathid — Thu, 08 Oct 2026 22:25:53 GMT

Effective internal communication requires both a compelling message and analytics to understand how that message is being received. Learning how employees engage with content, where communication gaps exist and which channels are the most effective can help employers determine whether teams feel connected or out of the loop.

Leveraging communications data can help leaders adjust their approach, personalize messaging and strengthen alignment across the organization. Below, Forbes Communications Council members share how they use data analysis to glean actionable insights that improve internal communications.

“Data analysis transforms internal communication from guesswork into strategy. By tracking engagement, like what messages resonate, who responds and how quickly, we identify where alignment gaps exist. Layering analytics with identity insights adds another dimension: understanding which teams or roles need what information, and when, to keep governance, security and operations moving in sync.” – Hope Frank, Gathid

1. Link Insights With Key Business Outcomes

Data is at the heart of our internal communications strategy. We continuously analyze engagement metrics and employee sentiment to see what truly resonates. By linking these insights with key business outcomes—like retention rates and quality scores—we identify which messages drive meaningful action. This closed-loop approach ensures every communication is both targeted and measurably effective. – Andrew Kokes, HGS

2. Connect The ‘What’ To The ‘Why’

Data isn’t just measurement; it’s empathy at scale. The best internal comms teams use data to understand how messages land, not just how often they’re read. Patterns in engagement reveal sentiment, trust and clarity gaps. The insight comes from connecting the “what” (metrics) to the “why” (context), and then using that feedback loop to make communication more human, not more automated. – Leeron Walter, Teramind

3. Find Out What Internal Audiences Crave

Data analysis is key to understanding if our internal communications strategy is resonating with our audience. From email newsletter open rates to the most popular messages and time on page, data helps us understand what our internal audience craves. The analysis can drive further messaging development and outreach frequency to engage our internal audiences. – Kimberly Osborne, Old Dominion University

4. Listen At Scale, Then Respond With Empathy

Data helps us listen at scale. It shows patterns in engagement, tone and timing—but meaning comes from empathy, not numbers. We look for signals of need, such as confusion, excitement and curiosity. Then we adapt how we communicate to meet that. Insight isn’t just what data says—it’s how we choose to respond with humanity. – Barbara Puszkiewicz-Cimino, SUMMIT One Vanderbilt

5. Replace Assumptions With Evidence

Data analysis allows me to move from assumptions to evidence-based decision-making. Rather than relying on anecdotal feedback, I use quantitative and qualitative data to understand how employees engage with messages. – Kurt Allen, Notre Dame de Namur University

6. Spot Patterns, Not Vanity Metrics

Data helps reveal what actually lands with the team. We track engagement on updates, meeting feedback and message clarity, then look for patterns instead of vanity metrics. The goal is to spot gaps in understanding or morale early and adjust communication style, timing or format before issues grow. – Prakriti Poddar, Roundglass Living

7. Use AI For Continuous Employee Listening

Internal comms pros should use AI for continuous listening by analyzing engagement data on employee content distributed through Slack, Teams, intranet and email. This data allows comms teams to understand employee sentiment and topics of interest on a more regular basis than the annual engagement survey. Weekly insights can be used to optimize comms strategy, channel mix and leadership responses. – Rekha Thomas, Path Forward Marketing

8. Turn Metrics Into Meaningful Stories

Data shows what matters and what moves people. I look at open rates, feedback and behavior to see what truly connects. Then I turn that insight into a simple story that explains why it matters, what is changing and what action to take. Clear visuals, plain words and relevance make data human and useful. – Marie O’Riordan

9. Apply Marketing Precision To Internal Comms

When we optimize internal communications the way we do external communications, everything changes. We stop treating employees as an audience to update and start seeing them as a community to engage. We already segment, personalize and test messaging for customers and prospects. That same precision applied internally creates culture, not just compliance. – Paula Mantle, Branch

10. Translate Engagement Data Into Action

Data should shape every internal conversation. We track engagement across tools like Slack and project dashboards to see where communication flows or stalls. Then we translate those metrics into actions by using more visual updates, shorter syncs or added clarity where teams need it most. Data turns feedback into alignment. – Jessica Wong, Valux Digital

11. Treat Employees As Internal Customers

When you treat employees like internal customers, the same data used in marketing becomes powerful for internal comms: open and click rates, engagement, retention, time saved and business gains. These signals reveal moments where information, celebration or intervention matters most. Layering automation on top of those insights turns data into a driver of real cultural impact. – Stephanie Bunnell, Local Language

12. Use Attendance Data To Bridge Hybrid Gaps

In-office attendance data are critical as organizations transition to in-person and hybrid work models. When staff are in the office, plan for experiential interactions—town halls, elevator screens and informal updates. With a fragmented workforce, internal communications teams must watch for silos, as in-person employees may receive information more quickly than their remote counterparts. – Ken Louie, MetroPlusHealth

13. Measure Attention, Not Just Awareness

Shift focus from simply sending messages to understanding and optimizing employee attention and resonance. We focus on behavioral metrics and sentiment analysis of internal feedback channels. If a crucial announcement has a high open rate but a low time on page or a delayed action rate, it tells us the content was seen, but the message was not clear or compelling enough. – Patrick Ward, Vanguard

14. Look For What’s Missing In The Data

Treat internal data less like a report card and more like an X-ray. Look for what’s missing, not just what’s performing. Track which messages spark follow-up, get repeated or shift behavior. Patterns of silence or distortion often reveal more than surveys. Use that to refine how, when and through whom messages move best. – Christina Mendel, ChristinaMendel.com

15. Track Resonance To Build Cultural Trust

Internal comms data is not just about reach; it’s about resonance. I track message-to-action rates and various signals of silence as indicators of indifference and trust loss. When employee belief and behavior align on values or a specific initiative, communication becomes governance intelligence that shows leaders where culture and trust are working. – Toby Wong, Toby Wong Consulting

16. Use Patterns To Refine Cadence And Tone

Data gives internal comms its direction. Tracking engagement, sentiment and timing reveals not just what’s read, but what’s retained and acted on. I look for patterns—spikes, silence or slow responses—to understand how messages land. Turning that into action means refining cadence, channel and tone so communication feels timely, relevant and human. – Katie Jewett, UPRAISE Marketing + Public Relations

17. Align Teams Through Layered Analytics

Data analysis transforms internal communication from guesswork into strategy. By tracking engagement, like what messages resonate, who responds and how quickly, we identify where alignment gaps exist. Layering analytics with identity insights adds another dimension: understanding which teams or roles need what information, and when, to keep governance, security and operations moving in sync. – Hope Frank, Gathid | Gathered Identities

18. Measure Action, Not Just Communication Reach

Data is our internal comms OS. We tag every message by audience, topic or CTA, track reach, cascade lag, read depth and implement a 24-hour “know what to do?” pulse. Weekly, we A/B test subject and format, ship a manager pack where depth is low and judge success by one metric: Comms Action Rate—the percentage who took the intended action. – Sanel Mezbur, Juice Ai

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