2026 to bring AI reckoning as value & trust trump hype
SAS has forecast that 2026 will be a pivotal year for artificial intelligence, predicting a period where organisations must address both returns on investment and ethical implications while adopting responsible approaches to AI deployment.
With rapid advances in generative AI technology throughout 2025, there were also significant challenges, including inflated expectations, project failures and rising operational costs. SAS experts suggest that the initial surge of excitement around generative AI has ebbed, and a more measured phase is emerging that will place a premium on demonstrable value and responsible governance.
Data centre costs
One of the key challenges identified concerns the sustainability of investment in data infrastructure. "Major investments in data centre buildouts will prove impractical as costs come home to roost; expectations were high, but resulting revenue wasn't enough to cover the expense. Tech companies angle for alternatives. Economics experts crow told-you-so," said Jared Peterson, Senior Vice President, Platform Engineering.
Accountability for AI spending
The financial scrutiny of AI projects is also expected to intensify. Manisha Khanna, Senior Product Manager, AI & Generative AI, stated, "The AI spending shake-up is coming. After billions wasted on ChatGPT wrappers and vapourware, CFOs are demanding real ROI - and most generative AI projects can't deliver. The honeymoon phase where 'AI innovation' justified any budget is over, replaced by brutal questions about cost per query, accuracy rates and measurable business outcomes. Companies that can't show concrete savings, revenue growth or productivity gains within six to 12 months will see their AI initiatives shelved, or their vendors replaced."
CIOs and integration
The evolving role of chief information officers was addressed by Jay Upchurch, Chief Information Officer. "In 2026, CIOs will answer the call to orchestrate the agentic AI future. As AI agents proliferate, the CIO's role will decisively shift from tech enabler to ecosystem integrator: the Chief Integration Officer. AI governance, integration and cross-functional leadership will shape the day of every CIO as we determine the future of IT architecture in an agent-led world."
Agentic AI enters the mainstream
Expectations for the workforce transformation underpin much of the shift. Udo Sglavo, Vice President, Applied AI and Modelling Research & Development, said, "As we mark half a century of innovation, resilience and growth, 2026 ushers in a new era of enterprises evolving into ecosystems where AI agents are no longer tools; they are teammates. Enterprises will be expected to operate with mixed human-AI teams, where agents act as trusted collaborators, executing tasks, sharing context and learning continuously alongside people."
The implications of these new AI colleagues were spelled out by Iain Brown, Head of AI & Data Science, Northern Europe. "By the end of 2026, Fortune 500 companies will be reporting agentic systems autonomously resolving more than a quarter of multi-step customer interactions. These agents won't just advise, they'll execute, with measurable revenue impact. That will also create new roles like Agent SRE and even Chief Agent Officer. The flip side is that the first major 'agent outage' will hit headlines, as organisations discover that when autonomous systems drive revenue, downtime has a price tag."
Empowering the workforce
Bryan Harris, Chief Technology Officer, stated, "Do you want to play to win, or not to lose? In 2026, leaders will face a spectrum between two options: either use AI to eliminate jobs or use AI to empower people to create a competitive advantage. It is becoming increasingly clear that AI should empower people - not replace them - and companies will need bold and inspirational leaders to invest in their workforce through continued change."
Responsible adoption and trust
The importance of responsible deployment and oversight was highlighted by Luis Flynn, Market Strategist for Applied AI, Open Source Software & ModelOPS. "Remember when the log4J breach rocked the open source community? In 2026, mature, early AI adopters that bypassed attempts to measure and incorporate AI responsibly will be exposed. The result will be a massive loss of credibility as their use of commoditised AI slop is surfaced to the masses."
"In 2026, the AI debate will no longer be one of innovation versus trust. As government regulation of AI remains inconsistent, corporate self-governance will extend to include the necessary guardrails to enable AI in the enterprise responsibly. The organisations that thrive won't simply be those that deploy AI first; it will be those that recognise the strategic reality that governance isn't a restraint on innovation, it's a necessary companion," said Reggie Townsend, Vice President, Data Ethics Practise.
AI architecture and energy requirements
On the subject of infrastructure, Marinela Profi, Global Agentic AI Strategy Lead, commented, "Global enterprises will demand control over their data, models and infrastructure. 'Bring your own model' and 'sovereign AI' setups - where companies run foundation models within their own governance and compliance boundaries - will become the default for regulated industries. In other words, the cloud stays, but the control shifts."
Infrastructure requirements are also challenged by the increasing energy demand. Franklin Manchester, Global Insurance Advisor, highlighted, "U.S. data centres will require an additional 29 gigawatts of power by 2027 to continue operating. Running at 90% capacity, a five-gigawatt data centre would consume as much energy as 3.65 million homes in one year. As other global powers invest in gigawatts of solar power per day, without increasing power capacity as quickly as possible, the U.S. will lose its ability to collaborate and advance in AI and data on the international stage in 2026."
Sector developments
Jennifer Chase, Chief Marketing Officer, noted, "By 2026, agentic AI - systems that act, decide and adapt autonomously - will move from pilots to the core of how organisations operate and serve customers. Those investing in the right infrastructure, governance and skills will unlock smarter decisions and seamless experiences. Those who don't will fall behind both in performance and in meeting customer expectations."
Amy Stout, Head of Quantum Product Strategy, added, "In 2026, the quantum market will heat up considerably as hopes rise that the technology will mature to early-stage value by 2030. Most investors will broaden their scope from hardware and post-quantum cryptography to a greater emphasis on software and applications. Meanwhile, keep your eyes peeled for the phrase 'quantum architecture': it encompasses the full stack of a quantum system, including the software and application layers that drive real-world quantum value. Expect to see hiring ramp up for in-house expertise to drive toward this future."
The competition for data assets was highlighted by Alyssa Farrell, Senior Director, Platform and Horizontal Solutions. "Synthetic data is not a workaround, but a strategic weapon against data scarcity, privacy limitations and compliance bottlenecks. In 2026, expect a data arms race, where companies compete not only on multimodal real-world data but on how convincingly they can create it. The winners? Those who master synthetic realism and shift at scale from experimental to essential capabilities that drive business advantage."
On workforce management, Jenn Mann, Chief Human Resources Officer, commented, "By 2026, HR leaders will manage more than people, they'll manage AI agents too. As agentic AI becomes part of daily workflows, HR will define new policies for onboarding, performance and collaboration between humans and digital coworkers. The future of workforce management will be hybrid-human and machine."
Market reckoning
"2026 will mark the start of AI's market reckoning - when hype collides with governance and only accountable innovation endures. The push for consistent ROI and transparent oversight will shutter vanity projects and reward the disciplined, refocusing investment on the fundamentals: data orchestration, sound modelling and explainable governance. Overhyped technologies will fade, replaced by responsible AI built for measurable impact and with operational rigour.
As AI hype gives way to AI accountability, only two questions remain - how deep will the reckoning run, and when will the renaissance begin?"
Stu Bradley, Senior Vice President, Fraud & Security Intelligence.
