Cequence Security said Anthropic, Dr. Chase Cunningham and Cequence have aligned on a behaviour-based approach to securing AI agents. It described this convergence as a shift in how the industry defines zero trust for agentic AI.

The shared view centres on a simple point: the main risk from AI agents lies not in whether they can log in, but in what they do after access is granted. The work of Anthropic, Cunningham’s research and Cequence’s AI Gateway architecture all point to controls that monitor and restrict runtime behaviour rather than relying mainly on authentication.

That marks a departure from traditional cybersecurity practice, which has focused on verifying identity at the point of entry. With autonomous software agents, the concern is that an authorised system may still carry out harmful actions, misuse APIs or remove sensitive data through approved channels.

The issue is drawing more attention as businesses move AI agents from trial environments into live operations. These systems are being used with access to internal tools, sensitive datasets and production systems, raising the stakes if an agent behaves unexpectedly or is manipulated by malicious prompts.

Cequence said this environment requires zero trust principles to be applied continuously throughout an agent’s activity. In practice, that means checking the context of each action, limiting the resources available to the agent and enforcing policy at the level of individual transactions.

Shreyans Mehta, Chief Technology Officer at Cequence Security, set out that argument directly.

“Most security teams are still trying to tackle AI risk with prompt detection and short-lived tokens – basically, really tight sign-in security. But that misses the point entirely. You can nail authentication and still get burned by an agent running amok inside the castle,” said Shreyans Mehta, Chief Technology Officer at Cequence Security.

Mehta also pointed to what he sees as broader agreement across the sector.

“Anthropic, Dr. Cunningham and Cequence all recognised early on that the gamechanger is securing agent behaviour. Seeing the whole industry pivot hard toward that truth, toward the approach we baked into the AI Gateway from day one, is the ultimate validation. It crowns the AI Gateway as the new reference architecture for the space,” he said.

Security model

Cunningham, who has published research on what he calls Agentic Zero Trust, framed the problem in similar terms. In his view, established controls focus too heavily on the “front gate” and do not address what happens once an AI system is inside a network or application environment.

“Traditional security controls focus obsessively on the front gate – who gets in. But with AI agents, the real damage happens after the front gate, through totally authorised channels,” said Dr. Chase Cunningham, a leading expert on Zero Trust security.

“You have to extend zero trust inside, to cover not just authentication, but every action an agent takes. Cequence’s AI Gateway is a huge leap toward that goal, toward getting zero trust to fully cover the AI agent threat model,” Cunningham said.

The broader technical argument is that AI agents can combine a series of individually permissible steps into harmful or unintended outcomes. Because those patterns may only become visible as they unfold, static rules or one-off login checks may not be enough to stop them.

That is why the behaviour-based model emphasises real-time monitoring and intervention. Instead of treating access approval as the main control, the system applies checks throughout the session, looking at which tools are being called, what data is being requested and whether the sequence of actions fits policy.

CIS guidance

Cequence also linked this thinking to the Model Context Protocol Companion Guide from the Centre for Internet Security. The guide adapts the CIS Controls to address risks that arise when AI agents interact with enterprise tools, systems and information, and identifies the protocol layer as an important point for governance.

According to Cequence, the guide calls for explicit tool-level permissions, audit trails for interactions and real-time protection for sensitive data. It said those ideas align with the design of its AI Gateway, which creates least-privilege agent profiles, records API activity and inspects requests and responses for sensitive information.

Mehta drew a direct link between the policy framework and implementation.

“The CIS MCP Companion Guide defines what enterprises should do; the Cequence AI Gateway operationalises it,” he said.

“The guide calls for explicit tool-level permissions, auditable interactions, and real-time sensitive data protection. AI Gateway delivers by generating least-privilege agent personas, logging every API call, and applying DLP scanning to tool requests and responses. It takes the CIS framework from theory to practice,” Mehta said.

The debate comes as security teams face a faster threat environment shaped by AI on both sides. Cequence argued that attack timelines are shrinking sharply, making immediate visibility into API calls and data flows more important as organisations deploy agents into business processes.

Cequence said its platform protects more than 10 billion daily API interactions and 4 billion user accounts.

Emma Reynolds is understood to have written to water regulator Ofwat on Monday warning the current bid tabled by Thames Water creditors would place an “undue burden” on customers.

The Government’s misgivings over the deal comes as Ofwat is said to have been close to accepting the offer from bidding consortium London & Valley Water, which has proposed injecting £10 billion into debt-laden Thames Water in return for any new fines over sewage leaks being waived for four years.

READ MORE: Thames Water ‘would need to pay £749m’ under controversial deal

Thames Water – Britain’s biggest water supplier with 16 million customers – is hoping to secure the deal to stave off temporary nationalisation after being left close to collapse by nearly £20 billion of debt.

It has also faced a series of hefty fines for its poor environmental performance in recent years.

A rescue bid by creditors is seen as the final realistic option on the table to avoid being placed into the Government’s so-called special administration regime after a previous rescue deal with US private equity giant KKR collapsed in May last year.

Administrators have already been lined up to step in if needed.

Ms Reynolds’s criticism of the deal centres on concerns that customers will lose out under the creditors’ offer, according to The Times, which first reported the details of the letter.

It is thought she raised worries that the creditors’ proposal was “weak”.

But the Government has repeatedly said it prefers a “market solution” over temporary nationalisation.

Ofwat and the Department for Environment, Food and Rural Affairs have been approached for comment.

The letter from Ms Reynolds comes in a difficult week for Prime Minister Sir Keir Starmer, with Andy Burnham – the mayor of Greater Manchester – hoping to win the Makerfield by-election on Thursday, which would pave the way for him to launch a leadership challenge.

Mr Burnham recently signalled he could bring in a 10-year plan to renationalise the water industry, saying reform is needed to put the public interest first.

A spokesman for Thames Water said: “We remain of the view that a market-led solution is the best way to secure the long-term stability needed to continue improving performance and advancing our turnaround plan, for the benefit of customers, the environment and our stakeholders.

“Our priorities remain on providing safe, resilient services for customers, supporting our colleagues and working closely with suppliers, government and regulators.”

It had been expected that the Government would give its backing to the Thames Water takeover this summer, with the utility fast running out of cash and said to be facing collapse within months if a deal is not forthcoming.

London & Valley Water’s proposed deal would see it inject £3.35 billion of new equity into Thames Water and up to £6.55 billion in new debt.

But it is said that Thames Water would also have to pay nearly £750 million to its creditors, lawyers and advisers as part of the restructuring.

AI has become more than just a bet on the future. Now, it’s how work gets done, especially with Webex.

Peter Diamandis once remarked how there’ll be two kinds of companies by the end of this decade. Those that are fully using AI, and those that don’t survive.

The gap is opening between organisations that are putting AI into everyday work, and those still treating it like something to explore in the future.

One group is moving much faster, making clearer decisions, and getting more done. The other is stuck in the pilot stage, building proofs of concept, and talking about what might be possible.

It’s the focus, rather than the technology, that’s changing.

AI has moved on from being a discussion about tools and started to become a conversation about execution.

These are now the key questions to consider:

• Where does AI show up in the average working day?
• Who uses it, and how often?
• Does it make work easier, or just add something else to manage?

Communication is where AI either works or fails

For most organisations, the answers sit in the communication layer. Think about meetings, messages, calls, customer conversations.

This is where time disappears. Decisions get made here, and customer experience can either be won or lost.

If AI doesn’t improve these moments, there’s rarely any change. That’s why the role of Webex itself is starting to shift.

Webex’s move from collaboration platform to AI execution layer

AI tends to fall when it lives outside the workflow. When it’s another platform to log into, or something owned by a small innovation team, usage tends to drop off. People default back to the familiar ways of working.

Webex takes an entirely different route by building AI into the tools people already use daily.

That shows up in practical ways. Notes, actions and follow-ups are automatically captured during meetings. Live transcriptions and summaries cut down admin tasks and reduce any confusion.

There’s also smarter messaging and collaboration processes that helps teams reach decisions faster. Alongside that, customer experience capabilities that improve routing, insight, and resolution also come into effect.

None of this is about adding clever features for the sake of it. It’s about giving people time back and reducing friction within work.

Why do partners make the difference?

Technology on its own doesn’t change behaviour. Partners do.

They understand how teams work, where the bottlenecks sit, and what outcomes customers really care about. That context is what turns AI from an idea into something people genuinely use.

Webex gives partners a way to embed AI into daily operations rather than selling it as an additional tool. It also moves the conversation away from licences and towards results.

What kind of results? How about shorter sales cycles, or better customer engagement. There’s a potential for higher employee productivity alongside clearer, more confident decision‑making.

That’s where real differentiation starts to appear.

What happens when AI is done properly

When AI is built into the workflow, the impact becomes obvious.

Sales teams spend more time with customers and less time writing up calls. Service teams can resolve issues faster because they have the full picture right in front of them.

Technology leaders see the patterns and insight instead of piecing together fragmented information. Employees also spend less time on low‑value admin tasks and more time on work that matters.

AI suddenly stops feeling like a headline topic and starts feeling like a real part of the working day.

A divide that’s already taking shape

Access to AI is an inevitability. What will really matter is who uses it in a way that genuinely changes business performance.

Webex, for example, is moving beyond being just a UC platform. It’s becoming an intelligence layer across meetings, messaging, voice, and customer experience.

Right now, AI integration into Webex is improving how people communicate and make meaningful decisions.

For partners, there’s an opportunity to lead customers through decisive change rather than just sell another product.

For customers, AI becomes something to rely on as opposed to just another tool to experiment with.

For employees, it’s the difference between feeling overloaded and feeling supported.

The divide Diamandis talked about? Turns out it’s already here. The companies that will pull ahead will be the ones quietly building AI into how work gets done. It all starts with the platforms that people are already using to communicate.

Get in contact with Gamma Communications and learn how Webex is transforming how businesses collaborate and prepare for the future of work.