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Joy Agwunobi
Businesses worldwide are preparing for a pivotal year as several emerging technology trends are expected to accelerate in 2026, reshaping how organisations operate, manage risk and deliver value.
According to insights from the Forbes Technology Council, the shifts ahead extend far beyond incremental technology adoption, pointing instead to deeper changes in workflows, accountability structures and trust in digital systems.
The council notes that enterprises are entering a phase where technology decisions are no longer experimental. Instead, they are becoming central to how work gets done, how systems communicate with one another, and how organisations demonstrate that digital tools are reliable enough to support real-world operations.
While artificial intelligence (AI) remains the most dominant force shaping the technology landscape, experts caution that its true impact in 2026 will depend on how it converges with governance, security, infrastructure and enterprise-wide accountability.
Members of the Forbes Technology Council say “business as usual” is already being challenged, with companies expected to rethink both strategy and execution as these trends mature.
Governance challenges threaten agentic AI adoption
One of the most critical issues identified for 2026 is the governance barrier facing agentic AI,autonomous systems capable of executing multi-step tasks without continuous human input. Kamal Anand, president and chief operating officer of Trustwise, warns that large enterprises may slow or halt adoption not because the technology fails, but because trust and auditability lag behind.
According to Anand, boards are increasingly demanding clear explanations of AI-driven actions, including the ability to trace what an AI agent did at specific moments in time. Without real-time oversight and detailed audit trails, many agentic AI pilots risk being quietly abandoned.
Ambient AI moves into everyday digital interactions
Another major trend expected to gain momentum is the shift toward ambient AI, where intelligence becomes embedded seamlessly into daily digital experiences. Brijesh Prabhakar, chief operating officer at Movate, says AI is on track to become inexpensive and ubiquitous, much like internet search in the early 2000s.
He adds that while the full societal implications remain uncertain, 2026 will be a significant year both technologically and socially. Early steps in edge inference processing data closer to where it is generated, are also expected to emerge during this period.
From experimentation to business accountability
Experts also anticipate a major reset in how AI investments are evaluated. Ryan Manning, chief product officer at BMC Helix, says expectations from CFOs, boards and investors are shifting decisively away from experimentation toward measurable business outcomes.
According to Manning, 2026 will mark the transition from crafting AI visions to delivering incremental results that impact enterprise economics. This change will be driven largely by the maturation of agentic AI, enabling organisations to rethink productivity, cost structures and operational efficiency.
AI agents embedded in core enterprise systems
Within enterprise software, AI is expected to move from the periphery to the core. Pranav Lal, head of business technology at Gusto, explains that AI-native enterprise applications will increasingly embed task-focused agents directly into systems such as customer relationship management, customer support and IT platforms.
Rather than operating as separate chatbots or pilot tools, these agents will draft outreach, update records, generate contracts, route tasks and trigger automated workflows using live operational context.
Security risks collide with AI ambition
As AI systems gain access to larger and more sensitive data pools, security tensions are expected to intensify. Jason Buffington, principal analyst at Data Protection Matters, notes that while AI can unlock insights from dormant or backup data, many organisations have not fully assessed the risk exposure this creates.
He warns that inviting AI agents to analyse critical data assets could prompt panic-driven restrictions once vulnerabilities become apparent, making 2026 a year where AI value and information security priorities directly collide.
Continuous trust verification becomes essential
Trust in AI systems is expected to move from periodic evaluation to continuous verification. Vin Sharma, founder and CEO of Vijil, says enterprises deploying AI agents in critical workflows will increasingly demand production-ready systems with built-in identity management, pre-deployment validation and runtime governance.
This marks a shift away from one-off red team tests toward continuous improvement models designed to maintain trust throughout an AI system’s lifecycle.
Cryptographic foundations underpin trustworthy AI
Several experts emphasise the role of cryptography in enabling safe AI adoption. Karim Eldefrawy, CTO and founder of Confidencial.io, highlights the growing importance of unified cryptographic approaches that combine encryption, isolation, digital signatures and least-privilege access controls.
These mechanisms, he says, are foundational for securing data, verifying AI outputs and limiting autonomous system behaviour in enterprise environments.
Infrastructure adapts to AI-driven power demands
AI’s expansion is also reshaping physical infrastructure requirements. Ravi Prasher, CTO at Bloom Energy, points out that traditional power grids were not designed to handle AI’s highly variable and intensive energy needs.
As a result, enterprises are increasingly considering distributed, on-site power generation, signalling a shift from viewing energy as a basic utility to treating it as a strategic component of infrastructure planning.
Smarter AI applications and autonomous decision-making
Karthik Sj, general manager of AI at LogicMonitor, predicts the emergence of long-running agentic applications capable of managing complex workflows, replacing poorly designed chatbot experiences. In parallel, John Davagian, CEO of L2L, expects AI to move beyond insights toward autonomous, real-time decision-making, particularly in manufacturing and supply chain operations.
IoT, orchestration and digital sovereignty gain prominence
Other trends expected to shape 2026 include the rise of AI-ready Internet of Things systems that centralise intelligence across operations, as well as a growing focus on orchestrating AI capabilities across vendors and platforms rather than choosing between buying or building solutions.
Digital sovereignty is also set to play a larger role. Mark Thirlwell of BSI Group notes that as regulations evolve, sovereignty considerations will increasingly be embedded into cloud, AI and data centre strategies worldwide.
Security threats intensify in the AI era
Cybersecurity is expected to become one of the most contested battlegrounds of the AI era in 2026, as experts warn that the same technologies driving efficiency and automation are also dramatically amplifying cyber risks. While many organisations are embracing AI as a defensive tool, industry leaders caution that attackers are moving faster and often more aggressively than defenders anticipate.
TK Keanini, chief technology officer at DNSFilter, warned that AI will not only intensify existing cyber threats but also create entirely new ones. According to him, phishing attacks are approaching near-perfection through the use of deepfakes, making it increasingly difficult for both individuals and organisations to distinguish legitimate communications from malicious ones.
Keanini added that AI-driven attackers are now capable of chaining together minor software flaws at machine speed, turning small vulnerabilities into major security breaches in a fraction of the time previously required. This evolution, he said, is accelerating the shift toward autonomous cyberattacks, where adversaries define an objective and allow AI agents to dynamically rewrite their own code in real time to bypass security controls.
Other experts shared similar concerns, noting that many organisations still place excessive confidence in AI-powered automation as a cure-all for cybersecurity challenges. Federico Simonetti, chief technology officer at Xiid Corp., observed that cybercriminals are already using AI to test tens of thousands of attack scenarios daily, far outpacing traditional defensive strategies. Treating AI solely as a defensive solution, he warned, could leave enterprises dangerously exposed.
At the same time, Ambuj Kumar, co-founder and CEO of Simbian, pointed to a shift in how security testing itself will evolve. He noted that traditional penetration testing has remained largely manual and limited in scope, but 2026 will likely see the emergence of automated, context-aware testing tools capable of mimicking real attackers. These systems, he said, will understand business logic, application state and chained exploits, behaving more like skilled human red-teamers than conventional scanning tools.
Together, these developments suggest that 2026 may mark a defining year for enterprise cybersecurity, one in which organisations are forced to confront the reality that AI is not just a defensive asset, but a powerful weapon in the hands of increasingly autonomous adversaries.
From pilots to profit-driven AI
Ultimately, Forbes Technology Council experts agree that 2026 will be defined by AI’s ability to deliver measurable impact. Rajesh Gharpure of Persistent Systems says organisations will increasingly judge AI by its contribution to profit and loss, while William Briggs, CTO at Deloitte Consulting, stresses that real transformation requires redesigning workflows rather than embedding old inefficiencies into new systems.
As highlighted by Forbes Technology Council, these expert perspectives collectively point to a future where AI and related technologies are no longer optional innovations but foundational elements reshaping how businesses operate, compete, and earn trust in a rapidly evolving digital economy.
