Industry leaders outline how AI will mature in 2026, shifting from experimentation to trusted enterprise deployment while forcing consolidation, regulation and a renewed focus on security and resilience.
Ed Keisling, Chief AI Officer Progress
1. AI Plumbing: As the models, frameworks and standards change, many solutions that have already been built will quickly become outdated, unsupported or insecure. There will be a significant effort to refactor these pilots which will impede new AI development.
Organisations will need to pause to work on the plumbing to define and build the new frameworks and standards needed for their organisations that are scalable, flexible and secure.
2. Employees will suffer from Change Management Fatigue: As employees adopt to a new way of working and potentially new roles, some will suffer from Germane Cognitive Load exhaustion, the mental effort required to process new information by integrating it with existing knowledge which promotes deep learning and understanding.
3. The Compounding Curve: The gap in productivity between the innovators and early adopters and the majority and laggards will quickly expand. The innovators and early adopters will become 10x’ers and organisations will need to come up with innovative ways to foster growth and learning to bring the rest of the organisation along.
4. Smaller is better: Models will continue to get larger and more capable but organisations will find the best value with smaller, tailored, more cost-effective models that they can deploy internally and at the edge.
5. The Hype is real and there is reality in the Hype: Generative AI disillusionment accelerates as there is more awareness of AI’s influence on the news cycle through LLM generated audio and video content.
The use of AI companions, the saturation of AI content in social media and adult use of LLM’s all result in more calls for regulation. Societal blowback of AI increases as the mid-term elections approach in the US.
6. Integrate or get left behind: Market disruption will begin with companies that offer non-integrated products. Offerings that lack integration and data or sematic ‘secret sauce’ will be most at risk.
Integrated platforms and solutions will gain share by unlocking the value of existing customer data across products.
7. AI hype fades, trust endures: There will be numerous ‘News at 11’ moments with AI as companies rush to release AI capabilities within their organisations.
This will lead to an enhanced focus on companies prioritising security, fairness, accountability and transparency. Trusted and Responsible AI becomes a competitive advantage.
Lee Caswell, Senior Vice President, Product and Solutions Marketing, Nutanix
The sovereign edge will continue to evolve.
AI is a force for more distributed infrastructure as AI moves out to process data generated at the edge. Enterprises will need to consider the global management, distributed security and remote recovery or destruction policies available for the sovereign edge and rely more on platform engineering to successfully achieve this.
As AI continues to skyrocket in adoption, businesses will look to find ways to process AI-related data locally. As a result, organisations will look to global management solutions with integrated security and edge resiliency to help keep this in check.”
Duncan Curtis, SVP GenAI, Sama
Fragmented AI ecosystem consolidates
In 2026, the fragmented AI ecosystem will begin to consolidate into a more cohesive AI supply chain. What exists today as disparate services with disconnected vendors will evolve into an integrated infrastructure built for speed, latency and continuous model evaluation.
This maturation will be driven by the recognition that AI development requires robust, redundant systems, lessons learned from supply chain disruptions during COVID. Companies will prioritise building resilient AI supply chains with clear lineage from data collection through model deployment.
Cognitive infrastructure becomes core AI development strategy
By 2026, high-performing AI companies will view their data workforces and human oversight systems as cognitive infrastructure, essential components of their innovation stack rather than back-office functions.
Companies will redesign workflows so human oversight enhances rather than slows AI development, creating systems where human expertise continuously improves model performance in production environments.
AI model makers must prove real business models
2026 will be the year model makers are forced to act like real businesses. The era of promising ‘revenue someday’ is over, with companies like Anthropic projecting US$20–26 billion and investors demanding clear paths to profitability.
This shift will separate viable long-term players from those unable to demonstrate sustainable business models, leading to consolidation in the foundation model space.
Trust and safety become product differentiators
‘Responsible scale’ will be the defining characteristic of successful AI companies in 2026. Trust, safety and governance will shift from compliance add-ons to core product features and competitive differentiators.
Elia Zaitsev, CTO, CrowdStrike
Prompt injection is defining the AI era, turning the AI interaction layer into a new attack surface. In 2026, AI Detection and Response will become as essential as endpoint detection and response, with organisations requiring real-time visibility into prompts, responses and agent actions.
Security teams will also face a surge in AI identities. Identity security built for humans will not survive this shift, forcing organisations to rethink how non-human identities are governed and secured.
Adam Meyers, SVP of Counter Adversary Operations at CrowdStrike, said adversaries are already investing in AI-driven vulnerability discovery, accelerating the discovery and weaponisation of zero-day exploits.
The defenders who succeed will be those using AI with the same speed and precision: detecting, patching and proactively hunting for zero-days as fast as they’re found.
Lee Myall, CEO, Neos Networks
“AI is about to reshape the UK’s connectivity landscape faster than most people realise. The traffic patterns we’re beginning to see around emerging AI and data-centre growth zones are fundamentally different, more volatile, more capacity-hungry and far less predictable than traditional cloud workloads.
Kailem Anderson, Vice President, Global Products and Delivery at Blue Planet, part of Ciena
2026 will see a move toward telco-specific AI models and digital twins, alongside new security risks around AI agent manipulation.
