Enterprise leaders are navigating a complex 2026 landscape marked by economic volatility, cautious optimism, and immense pressure to accelerate the adoption of transformative technologies, according to a new paper from the IBM Institute for Business Value. The findings, based on surveys of more than 1,000 C-suite executives and 8,500 employees and consumers, reveal a striking contrast in sentiment: while only about a third of executives are optimistic about the global economy, an overwhelming 84% express confidence in their own organization's future performance.[1] This confidence is underpinned by a strategic pivot toward three interconnected trends expected to define the immediate future: the operationalization of agentic artificial intelligence, the critical establishment of sovereign data and AI policies, and the imminent arrival of commercially viable quantum computing.

The transition from experimental AI to agentic AI is emerging as a primary strategic goal for enterprises. These advanced AI systems, capable of independently planning, reasoning, and executing complex tasks, are being moved from isolated pilots into the core of business operations.[2][3][4] Executives are forecasting a substantial increase in AI-driven work, with AI-enabled workflows expected to surge from 3% to 25% within the year.[3] A recent IBM study found that AI investment is projected to grow from 12% of IT spending in 2024 to 20% by 2026, with 64% of these budgets now aimed at core business functions rather than scattered experiments.[3] By 2026, 83% of executives anticipate that AI agents will significantly improve process efficiency and output.[3][5] This optimism is largely shared by employees, who are showing a clear readiness to embrace AI in the workplace. The IBM survey found that twice as many workers would embrace, not resist, greater use of AI, viewing it as a tool to eliminate repetitive work and learn new skills.[1] Specifically, 61% of employees reported that AI makes their jobs less mundane and more strategic.[1] However, for agentic AI to succeed, leaders acknowledge significant hurdles, including the need for data architectures that support real-time insights and granting agents access to core enterprise systems like ERP and CRM platforms.[2]

As organizations rush to integrate AI, a critical gap has emerged between the pace of adoption and the implementation of necessary security and governance. This has given rise to a new strategic imperative for 2026: AI sovereignty. Defined as an organization's capacity to control and govern its AI systems, data, and infrastructure, this concept is now a boardroom priority.[1] According to IBM's research, an overwhelming 93% of executives state they must factor AI sovereignty into their 2026 business strategy.[1] Concerns over data residency and the jurisdiction of cloud services are compelling leaders to rethink where their models run and where their data resides.[2] The risks associated with inadequate governance are substantial. Another IBM report highlights that 63% of breached organizations lack a formal AI governance policy.[6] Furthermore, data quality remains a persistent barrier; nearly half of executives cite data inaccuracies and bias as an impediment to adopting agentic AI.[7] The consequences of failing to address these issues are stark, with Gartner predicting that 60% of AI projects unsupported by "AI-ready" data will be abandoned by 2026.[7] This focus on data integrity and control extends to consumer relations, as the report notes that customers are prepared to reward or penalize brands based on how their personal data is utilized.[2]

Beyond the immediate software revolution in AI, IBM forecasts that 2026 will mark a significant tipping point for quantum computing. The company predicts the emergence of "quantum advantage," the moment a quantum computer can solve a practical problem more efficiently or accurately than any classical supercomputer.[8][1][9] This is no longer a distant scientific goal but an engineering reality, driven by concrete hardware advancements.[8] IBM is advancing this frontier with processors like its new 'Nighthawk,' which features 120 qubits and enhanced connectivity, enabling it to run more complex quantum circuits with low error rates.[10][11] The company's roadmap projects the ability to handle workloads of 7,500 two-qubit gates by 2026, with a clear path toward a fault-tolerant quantum computer by 2029.[8][10][11] The first industries expected to benefit from this quantum leap are chemistry, materials science, and complex optimization problems.[8] IBM stresses, however, that unlocking the full potential of quantum computing will not be a solitary endeavor. The immense computational resources, data sets, and expertise required mean that progress will depend on the strength of broad ecosystems combining public and private sector expertise.[1]

In conclusion, the path to 2026 for enterprise leaders is one of navigating profound uncertainty by embracing disruption. The IBM report paints a clear picture of a business world moving with urgency to operationalize AI, establish robust data governance, and prepare for a new era of computation with quantum systems. While economic headwinds persist, a significant majority of leaders are pushing forward, redesigning operating models and re-skilling their workforces to capitalize on these next-generation technologies. The findings suggest that the most successful organizations will be those that not only adopt agentic AI and quantum computing but also build the foundational data policies and sovereign controls necessary to harness their power responsibly and effectively.