# Ajay G.

Ajay G. writes about cybersecurity for small and mid-sized businesses, especially endpoint security, compliance, and protecting company data when AI agents use business tools. Ajay's posts also describe building security products at Kitecyber.

- Profile: https://b2binfluencer.marketing/creators/ajay-g/
- LinkedIn: https://www.linkedin.com/in/ajaygulaticyber
- LinkedIn followers: 14,610
- Topics: artificial-intelligence, supply-chain, cybersecurity, ai-governance, ai-agent-security
- Based on 16 dated posts, latest 2026-10-01

## Summary

Most useful for SMB endpoint and AI-agent data security thought leadership and practical frameworks.

- Best for: A security vendor selling endpoint and AI-agent data protection to SMBs for thought leadership or a webinar.
- Not for: Fortune 500 identity-governance vendors targeting large-bank CISOs with video, newsletter takeovers, or guaranteed reach.
- Check first: Confirm LinkedIn follower analytics, recent post impressions and engagement, and any webinar attendance data.

### Takeaways

- SMB security needs fundamentals and integration, not a bigger stack.
- AI agents decide faster than security can respond.
- No single control sees the whole action.

## Main ideas

- **SMBs need security fundamentals and integration, not a bigger stack**: Ajay's most repeated position is that cybersecurity has earned a reputation for complexity, and small and mid-sized businesses absorb the cost. The question customers ask — what is the minimal set of tools needed to feel secure and meet compliance needs — should be simple to answer, but Ajay argues it has been made hard. Most SMBs, in this view, do not need dozens of tools or deep security expertise; they need clarity, consistency, and coverage. The trap is that each fundamental gets solved with a separate point product for endpoint, identity, compliance, and monitoring, recreating the complexity it was meant to remove. Ajay describes the same pressure from the staffing side: modern SaaS, GenAI tools, coding agents, browser extensions, and cloud services running on SMB-grade staffing produce too many tools, too many tickets, too little time, and too much risk, while compliance expectations move downmarket and qualified security talent stays scarce.
- **AI agents decide faster than security can respond**: Ajay argues that most data loss prevention was designed for humans and that agents invalidate its assumptions. Agents open files, read spreadsheets, call tools, and move content under a user's own login at machine speed. To existing tools, that activity can look completely normal because it uses legitimate permissions. The operative question shifts from whether sensitive data moved to who or what moved it, why, and whether that action should have been allowed. Ajay sets out what a control has to do to keep up: classify data the moment an agent touches it on the device; distinguish whether a person acted or an agent acted as that person; allow, warn, or block before anything leaves; and keep tracking the data after it is converted, encoded, or screenshotted. The framing is a race between agent speed and security speed.
- **No single control sees the whole action**: Ajay's recurring diagnosis of the fragmented stack is that each tool observes only a slice. Endpoint detection sees the process, data loss prevention sees the data, and the secure web gateway sees the connection, but nobody sees the whole action when an agent moves through several systems in one sequence. Ajay proposes correlating user, device, application, data, process, and network activity where the action happens, rather than adding yet another specialized AI security tool. The same idea appears in compressed form in a product launch post as a three-word loop: see, decide, enforce, continuously — with every attempt to read, copy, transform, upload, or share sensitive data by a human, a copilot, or an autonomous agent evaluated in real time and enforced on the spot.
- **Passing an audit is not the same as protecting data**: Ajay draws a line between compliance scope and what actually happens to data. Controls can be tested, audited, and passed while data still leaves through a route the audit never examined — the endpoint, the browser, or a generative AI prompt. Ajay argues that the proof itself should change: which controls get revisited and what that proof should look like. The theme also appears in lightweight documentation and continuous assessment as compliance fundamentals, and in automatic generation of audit-ready proof as a product capability.
- **Enforcement belongs at the endpoint, delivered through one agent**: Ajay's proposed architecture follows from the context-gap and agent-speed arguments: the decision should sit where data actually moves, at the endpoint, not in gateways, prompt filters, or network appliances that see only part of a sequence. The delivery model is a single lightweight endpoint agent carrying data loss prevention, endpoint management, secure web and SaaS access, and zero-trust private access, with no gateways, appliances, or new infrastructure to deploy. The unified endpoint management material lists the same approach in operational detail: automatic enforcement of SOC 2, ISO 27001, and HIPAA policies; one agent handling compliance, device security, onboarding and offboarding, and remote access; cloud-native operation independent of Active Directory or legacy network dependencies; pre-built compliance templates; and support for Mac, Windows, and Linux with disk encryption, screen lock, admin privilege, SaaS monitoring, and GenAI usage controls.
- **Agents could be how small companies compete — if someone governs them**: Ajay steps back from controls to argue that agents matter most for smaller businesses. The shift is from AI as a copilot that helps people write, research, or answer faster to agents that take a goal, use a browser and other tools, reach into business systems, learn workflows, and carry out multi-step work. The consequence is economic: a small company historically could not afford dedicated teams for every function, such as go-to-market, data analysis, lead generation, sales, or ad management, and agents could change that equation. Ajay pairs the opportunity with governance: when every SMB has dozens of agents acting across SaaS applications, company data, and the internet, the questions become what those agents can access and what actions they are allowed to take.
- **Your suppliers' security is your exposure**: One post moves outside endpoint and agent themes to argue that internal security is not enough: an attack on a software or service supplier can hit customers hard. Buyers should check that their suppliers are paying attention to security and compliance before an incident in someone else's infrastructure becomes an operational outage.

## Work to read

- [What an SMB actually needs to be secure and compliant](https://www.linkedin.com/posts/ajaygulaticyber_cybersecurity-smb-compliance-activity-7466983837026160640-yRnK)
- [You can pass a SOC 2 Type II audit and still leak data](https://www.linkedin.com/posts/ajaygulaticyber_you-can-pass-a-soc-2-type-ii-audit-and-still-activity-7498140341867278336-2dUz)
- [The context gap: why general AI broke endpoint security](https://www.linkedin.com/posts/ajaygulaticyber_the-context-gap-why-gen-ai-broke-endpoint-activity-7511119266356793344-oHua)
- [Agent speed vs. security speed](https://www.linkedin.com/posts/ajaygulaticyber_aiagents-datasecurity-dlp-activity-7507954952544145408-mrNX)
- [Launching AI Workflow Security with USA Today coverage](https://www.linkedin.com/posts/ajaygulaticyber_aiworkflowsecurity-aiagents-genai-activity-7485123768542195712-883_)
- [How to evaluate data security in the age of AI agents](https://www.linkedin.com/posts/ajaygulaticyber_how-to-evaluate-data-security-in-the-age-activity-7511552731917012992-Cjsb)

## Brand relationships

- **Kitecyber** (employment)
- **SourceForge** (mention)
- **Hyperagent** (mention)

## Partnerships

The LinkedIn posts show Ajay G. promoting Kitecyber’s own products: a launch of AI Workflow Security that received USA Today coverage, a unified endpoint management product, and a single lightweight agent that handles DLP, endpoint management, secure web and SaaS access, and zero-trust private access. Posts also point readers to third-party coverage in SourceForge and Slashdot and invite them to get in touch about IT, security, and compliance simplification. The posts don’t state rates, deliverables, editorial terms, booking lead times, sponsor approval steps, or who handles partnership requests, so ask Ajay G. directly about the operational terms. They show a clear subject lane a partner could build on: AI agents acting under user credentials, DLP that reacts only after data moves, endpoint-level visibility, and compliance for resource-constrained SMBs. Treat these as topic context, not a confirmed offer to collaborate.

## Alternatives

- Anne Bisagno: Choose Anne Bisagno over Ajay G. when a webinar targets leadership and governance rather than security engineering. Bisagno's two Posts frame BYOD and device trust as business resilience and governance initiatives, not IT decisions. They argue that identity and device posture—not network- and password-centric controls—reduce risk in hybrid work. A vendor selling an endpoint agent to regulated industries, with CIOs, risk owners, or HR-adjacent leaders as buyers, will find a natural fit: the session can focus on policy, employee experience, phased Zero Trust adoption, and how to start without rebuilding infrastructure. That is a different entry point from Ajay G.'s machine-speed agent problem, and an easier one to defend to a compliance-driven audience. The tradeoff: Bisagno's material does not address what happens when an AI agent reads files, calls tools, and moves data under a user's login. A joint session would cover device trust and BYOD governance, but Ajay G.—not Bisagno—makes the case that existing DLP reacts after data leaves and that enforcement must sit at the endpoint where the action happens. Expect to lose the agent-speed hook and the technical enforcement detail a product-led webinar usually needs.
- Cole McMillan: Choose Cole McMillan over Ajay G. when the campaign needs a documented, hands-on operating model rather than a threat framing. McMillan's Posts describe a full Microsoft environment build: a migration from reseller-managed Microsoft 365 licensing to a direct CSP model; a standardized identity-attribute scheme feeding dynamic groups; Intune enrollment; BitLocker, Defender, firewall, and update rings; Windows LAPS; and Conditional Access policies deployed in report-only mode before enforcement. One post details a single admin running IT for 150 users across multiple sites without a managed service provider, with stated results: roughly 4x ticket volume from centralized intake, about 90% faster first response, and about 60% less time to resolution. If the campaign needs to explain how a small team actually runs IT, McMillan's firsthand numbers and build sequence answer the question that Ajay G.'s Posts mostly raise. The tradeoff: McMillan's content centers on the Microsoft stack and IT operations, not agent data security or AI-specific DLP. A webinar with McMillan would lean toward identity, licensing, and endpoint configuration for Microsoft-centric administrators, rather than the vendor-neutral who-moved-this-data argument that makes Ajay G. a fit for an AI-agent data-protection sponsor. Buyers who do not run Microsoft 365 as their core platform will find less to use, and the session's product story shifts from data enforcement to environment governance.
- Arvind Suthar: Choose Arvind Suthar over Ajay G. when a webinar targets government, defense industrial base, or heavily regulated buyers whose purchases are driven by compliance obligations. Suthar's Posts show a sustained practitioner publishing practice: a continuously updated "Securing GCC High" reference, now described as 793 pages, with release notes covering a 75-check security assessment across six pillars mapped to CMMC, HIPAA, CJIS, and SOC 2; a full CMMC control set; Conditional Access policies mapped to each 800-171 control; phishing-resistant MFA and patch cadence; and Purview data-readiness before turning on Copilot in GCC High. The CMMC Phase 2 pause post argues that hygiene controls cost the same with or without controlled unclassified information and separates basic hygiene from the expensive compliance tail. For a sponsor whose buyers must show an assessor evidence, Suthar's control-mapping practice and free documentation asset are a stronger draw than a general SMB pitch. The tradeoff: the material stays within the GCC High and CMMC lane, so a sponsor targeting ordinary small and mid-sized businesses will reach a narrower audience, and the conversation centers on compliance rather than agents acting under a user's login. Ajay G. reaches non-regulated SMB and mid-market buyers with the agent-risk and audit-scope argument; Suthar reaches regulated buyers with control evidence and documentation. Pick based on which audience the campaign is paying to reach.

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AI-assisted summary of public posts. Audience demographics are not available. Engagement appears only where we checked recent posts. Method: https://b2binfluencer.marketing/methodology/