AI agents will fundamentally transform enterprise operations
We’re moving into an era where artificial intelligence isn’t just a feature, it’s an integral partner in the way enterprises function. The shift is already underway. We’re seeing enterprises move beyond isolated pilot programs or tool-based automation. By 2026, the dominant model will be embedded AI agents, semi-autonomous software systems that operate within the core of business operations, not outside of them.
These agents will work across functions, IT operations, cybersecurity, code development, customer service, and they won’t replace humans. They’ll work alongside them. That’s the point. AI will handle the repeatable tasks, the processes that demand speed, and systems-level monitoring. People will focus on high-value decisions, innovation, and strategy, the areas where judgment, ethics, and creativity still matter. You’re not choosing between humans or AI. You’re building with both.
This calls for a major reframe in how companies structure teams. The change is less about hiring different people and more about training leadership to rethink workflows, responsibilities, and where human cognition fits into the system. That’s where the real performance gains will come from. We’ll call it Human+. And it’s already being adopted at scale.
Carl Kinson, UK&I CTO at DXC Technology, said this clearly: “The rise of AI agents will reshape entire business value streams.” He’s right. Kinson explains that AI will be present across all levels, from customer-facing use cases to deep back-end operations, and DXC is actively embedding agents into its enterprise client systems. These aren’t chatbots or scripts. They’re machine collaborators that make decisions, respond in real time, and evolve with your business.
Let’s think ahead. Orchestration of multiple agents across teams will require new governance models. Data access, standardization across tools, and accountability must scale with automation. Success in this environment won’t come from having the best technology, it’ll depend on leadership’s ability to build cultures that adapt, stay curious, and innovate constantly.
The takeaway here is straightforward: If you want an organization that survives beyond 2026, you don’t need to catch up. You need to lead. Adopt AI agents not as a convenience, but as a design principle for how your business operates. Strip out inefficiency. Scale creativity. Move fast.
AI agents will enhance retail experiences by bridging digital and physical channels
Retail is going through a structural change, technology is catching up to what customers already expect. People are used to seamless digital experiences. Now they want that same level of relevance and efficiency in-store. By 2026, this expectation will become standard. AI agents will be central to delivering it.
Here’s what’s changing: customer apps, loyalty programs, and shopping preferences, things that used to operate in silos, are being connected. Retailers are starting to use opt-in data more intelligently, linking digital touchpoints with what happens on the physical shop floor. When deployed well, AI agents will turn this data into action. Not flashy gimmicks, useful interactions. Store staff informed in real time. Personalized alerts that are timely and relevant. Faster service, fewer steps.
The shift isn’t speculative. Mike Fantis, VP Managing Partner at DAC Group UK, pointed out that consumers are already engaging with this ecosystem. Loyalty schemes, click-and-collect, saved wishlists, these are entry points. Fantis said the industry now needs to think more ambitiously: “There’s so much more we could do… perhaps 2026 will be the year that retailers start being more ambitious.” He’s not talking about complexity. He’s talking about execution that matches customer expectations.
AI agents are already helping consumers at the top of the funnel, comparison shopping, product discovery, and even generating customized recommendation lists. Over the next two years, agents will complete more of the purchase journey on behalf of customers. Shopping lists become automated orders. Preferences become transactions. What matters here is convenience. That’s the consistent driver of engagement.
For executives, this means re-thinking the structure of digital operations and retail workflows simultaneously. You’re not optimizing a website or a store. You’re optimizing for a world in which AI agents act as intermediaries for individual customers. That includes everything from inventory systems being responsive to predictive signals, to store staff being supported by technology that doesn’t slow them down.
Fantis also noted that tools like Google Duplex already perform practical tasks on behalf of users, scheduling appointments and confirming availability. These are not experimental features. They’re live, operational systems. Retailers that recognize this shift and adapt customer support, inventory logistics, and service models accordingly will capture more share as this AI-driven behavior becomes mainstream.
The opportunity isn’t about novelty, it’s about precision, speed, and relevance. If retail brands can deliver those consistently, they stay in the game. If they can’t, automation will route customers elsewhere.
AI agents necessitate a cybersecurity transformation through modern identity-centric frameworks
When enterprises begin deploying AI agents across critical workflows, the security landscape changes immediately. AI agents don’t follow human patterns. They operate fast, around the clock, and interact with sensitive systems. That’s not a risk you can manage using legacy identity or access models built for static devices and employees. You need a framework where identity applies equally to people, code, and autonomous agents.
By 2026, enterprises that fail to modernize their identity architectures will face growing exposure. Every AI agent introduced into a business system becomes a potential attack vector if it’s not properly authenticated, monitored, and governed. These agents need unique digital identities with defined access privileges and constant oversight. Not a one-time setup, ongoing lifecycle management.
Matt Rider, Global VP of Customer Technical Support at Exabeam, made this clear: “During 2026, we’ll see identity-first security move beyond users and devices to include APIs, machine identities, and AI agents.” What that means is this, governance must now extend to AI behavior. Effective monitoring isn’t just about logging events. It’s about detecting intent, even when it deviates from expected patterns.
Traditional identity and access management systems were built for predictable interactions. But AI agents aren’t predictable by default. They’re trained on data and often act based on contextual awareness that isn’t linear. Enterprise leaders need tools that can track anomalous access, policy violations, or rogue automation attempts, even when it’s a system, not a person, initiating those actions.
Here’s what leadership should focus on: First, build identity stacks that treat AI agents as equal to human users, because that’s how they’ll interact with enterprise infrastructure. Second, unify identity across platforms so control doesn’t operate in isolated silos. Third, implement real-time permission management that makes change control as dynamic as AI operations themselves.
This isn’t just a defensive posture, it’s a foundation for scale. You can’t deploy hundreds of agents company-wide if each one becomes a blind spot. Accurate identity mapping, permission enforcement, and transparent monitoring are what bring confidence to automation.
The future of enterprise resilience will be defined by how well organizations govern not just who acts but what acts, and under what conditions. AI changes the attack surface. It also changes how accountability must be managed. The organizations that lead here will grow faster and remain secure in a world that moves quicker every month.
New AI-specific threat patterns, including agent-in-the-middle attacks, call for revised security protocols
As AI agents become active participants in daily workflows, especially in sensitive or business-critical environments, organizations must adapt their cybersecurity strategies. These agents don’t just fetch tools or organize data, they can view systems, take actions, and make decisions on behalf of users. That level of autonomy introduces new risks, including a serious one: the agent-in-the-middle.
This threat emerges from a simple fact, AI agents operate with user-level authority. Once compromised, a malicious or cloned agent can mimic legitimate actions, access systems, alter data, or manipulate workflows while appearing authorized. Detecting these actions becomes difficult if your systems can’t distinguish not just who is acting, but what the intent behind the action is.
Andre Durand, Founder and CEO at Ping Identity, addressed this directly: “As AI agents become part of daily workflows, a new threat is emerging: the agent-in-the-middle. These agents can see screens, move cursors, and act on our behalf… It’s the next evolution of man-in-the-middle attacks, only now, the intruder is software you invited.” He explained that digital trust will no longer depend on identity claims alone, it will hinge on verifiable proof of origin, policy adherence, and user consent.
This redefines accountability in security systems. Verifying that “something happened” isn’t enough. You need to validate who or what made it happen, under what rules, and with whose approval. That goes beyond standard authentication. It means building systems that continuously map behavior to intention and flag deviations in real time.
For C-level executives, this impacts several operational layers. First, every AI agent interacting with internal systems must be continuously validated, not just on login but throughout the session. Second, policies must define what an AI agent is allowed to do, and those policies need to be enforced by design, not bolted on afterwards. Third, logs must evolve into real-time forensic systems. Visibility can’t lag behind automation speed.
Leaders who treat identity as the core infrastructure layer, not just an IT feature, will be better positioned. The successful organizations in 2026 will be those that validate not just the digital identity of every actor, human or AI, but verify intent before granting real authority. That level of precision is what modern threat environments require. The future of security is less about stopping tools and more about proving trust.
Key takeaways for leaders
- AI agents will reshape enterprise operations: Leaders should embed AI agents directly into core systems to automate workflows, enhance IT operations, and scale customer service, freeing teams to focus on high-impact strategic work.
- Retail will prioritize AI-driven personalization: Executives must align digital and in-store operations around customer data, using AI agents to deliver more relevant, real-time experiences that boost conversion and loyalty.
- Identity must evolve to secure AI at scale: Organizations should transition to identity-first security architectures that treat AI agents as authenticated, monitored actors with tightly governed permissions to prevent misuse.
- New AI-driven threat models require active intent verification: Security leaders must adapt to emerging threats like agent-in-the-middle attacks by implementing continuous verification of agent behavior, identity, and decision intent across platforms.
