Enterprise technology is entering a new phase. After years of experimentation with AI, organisations are starting to move beyond the proof-of-concepts and into real-world deployment.
AI is already embedded into day-to-day operations and key conversations are shifting away from capability, towards governance, accountability, cybersecurity, and trust.
I recently sat down with Chris Steffen, Vice President of Research, VP of Research: Information Security, Risk and Compliance Management, at Enterprise Management Associates (EMA), to discuss the technologies shaping the future of enterprise IT.
Our conversation explored everything from agentic AI and machine identity to digital transformation and cybersecurity governance. One key theme surfaced throughout: while technology continues to evolve at an extraordinary pace, organisations are still working to catch up.
Understanding How Enterprises Really Adopt AI
Much of Steffen's current research focuses on a challenge that many organisations are now facing. While businesses often speak confidently about their AI and cybersecurity strategies, the reality of implementation can look very different.
Rather than focusing solely on technical capability, his work examines how organisations actually adopt emerging technologies in practice and where that process begins to break down.
"I am currently researching how enterprises actually really adopt cybersecurity technologies (compared to how they "SAY" they actually are using them), especially AI's move from experimentation to real operational use. I've been doing a lot of work in agentic AI, machine identity and cybersecurity governance, and why digital transformation stalls. Mostly, I am trying to understand where technical capability and maturity is outrunning organizational readiness — and what closes that gap."
Enterprise AI Is Entering Its Next Phase
For the past several years, AI has largely been characterised by experimentation. Organisations have explored use cases, launched pilot programmes, and tested new tools across their businesses. According to Steffen, that period is beginning to give way to something more mature as enterprises focus on embedding AI into long-term business strategy.
"Enterprises are moving from experimentation to operationalization. Budget is shifting from pilots toward embedded AI infrastructure, governance frameworks, and measurable ROI — a maturation phase separating durable investment from last year's hype-driven spending."
Why Agentic AI Is Dominating the Conversation
Among the many technologies shaping enterprise IT, agentic AI has become one of the most widely discussed. While Steffen believes the attention is justified, he also cautions against expecting organisations to move as quickly as the headlines often suggest.
"Agentic AI dominates attention, and it's largely justified — but overhyped in timeline. The underlying shift toward autonomous, task-completing systems is real; expectations for near-term enterprise-wide deployment remain ahead of actual readiness."
Machine Identity Is Becoming the Next Major Security Challenge
While AI continues to dominate industry discussions, Steffen believes another trend deserves far greater attention. As organisations deploy increasing numbers of AI agents and automated systems, machine identities are growing rapidly—bringing with them a new set of security challenges that many organisations have yet to address.
"Machine identity management deserves far more scrutiny. As AI agents proliferate, non-human identities now outnumber human ones significantly, creating an under-governed attack surface most security teams haven't yet architected for."
From AI Capability to AI Governance
The conversation around artificial intelligence has also matured considerably over the past year. Businesses are no longer asking only what AI can achieve—they're increasingly considering how to govern, measure, and manage it responsibly as deployments become more widespread.
"Twelve months ago, conversations centered on generative AI capability and productivity gains. Today, they've shifted decisively toward governance, agentic autonomy, cost accountability, and trust — from "what can it do" to "can we control it.""
Why Digital Transformation Still Falls Short
Despite significant investment in digital transformation, many organisations continue to encounter familiar obstacles. Legacy infrastructure, fragmented ownership, and organisational change remain significant barriers to success.
Steffen believes businesses often underestimate the operational changes required to support new technology.
"Legacy integration remains the persistent bottleneck. Organizations underestimate data readiness and change management, treating transformation as a technology purchase rather than an operational redesign requiring cross-functional ownership and sustained executive commitment."
Technology alone, however, is only part of the equation. Successful implementation depends on maintaining a clear focus on measurable business outcomes.
"Successful adoption ties technology to a specific business outcome with clear ownership and measurement. Failed implementations chase capability for its own sake, skipping the workflow redesign and training that adoption actually requires."
Identity Is No Longer Just an IT Problem
Identity has become one of the defining challenges of modern cybersecurity, yet Steffen believes many organisations continue to approach it using outdated assumptions. As attackers increasingly target credentials rather than traditional malware, identity governance has become central to enterprise security.
"Many still treat identity as a perimeter control rather than the primary attack surface. Businesses underestimate how credential compromise, not malware, drives most breaches — and underinvest in identity governance accordingly."
Humans Will Become Managers of AI
As AI systems become increasingly autonomous, the relationship between humans and technology will continue to evolve. Rather than simply using AI as another workplace tool, employees will increasingly oversee autonomous systems responsible for completing specific tasks.
"The relationship is shifting from tool-use to delegation and supervision. Humans increasingly manage AI agents as collaborators handling discrete tasks, requiring new oversight skills rather than direct execution skills."
Looking Towards the Future
Steffen is particularly interested in how agentic AI develops within highly regulated industries, where governance, compliance, and accountability become just as important as technical performance. These sectors are likely to provide the clearest indication of how ready organisations truly are for autonomous systems.
"I'm closely watching agentic AI's move into regulated, high-stakes workflows — finance, healthcare, legal — where autonomous decision-making meets compliance requirements, and where trust infrastructure will be tested first."
Looking further ahead, Steffen believes one concept will ultimately define the next generation of enterprise technology.
"Trust infrastructure will define the next era — governance, verification, and accountability systems for autonomous AI. Technical capability has outpaced organizational readiness; closing that gap becomes the defining competitive advantage."
Final Thoughts
Throughout our conversation, one message remained remarkably consistent: the future of enterprise technology won't be determined solely by how quickly organisations adopt AI, but by how effectively they govern it.
Whether discussing agentic AI, cybersecurity, machine identity, or digital transformation, Steffen continually returned to the same challenge. Technology is advancing rapidly, but organisational readiness has yet to keep pace.
As enterprises move beyond experimentation and into large-scale deployment, success will increasingly depend on building the governance, accountability, and trust needed to support autonomous technologies. Closing that gap won't simply improve AI adoption, it will become the defining competitive advantage of the next era of enterprise technology.
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