IBM cites agentic AI, data policies, and quantum as 2026 trends

Enterprise leaders are entering 2026 with an uncomfortable mix of volatility, optimism, and pressure to move faster on AI and quantum computing, according to a paper published by the IBM Institute for Business Value. Its findings are based on more than 1,000 C-suite executives and 8,500 employees and consumers.

While only around a third of executives are optimistic about the global economy, more than four in five are confident about their own organisation’s performance in the year ahead.

Executives expect to make faster decisions and are willing to redesign operating models, while employees are broadly positive about AI in their working lives. Customers, in turn, are ready to reward (or punish) brands based on how companies use their data.

Trend 1: agentic AI a strategic asset

Agentic AI is emerging as one of the main tools leaders expect to use in the coming year, and most execs say AI agents are already helping them.

However, for agentic AI to succeed, the expressed opinions state:

• Data architecture needs to support near real-time insight, not periodic reporting.
• AI agents’ success will depend on access to core systems (ERP, CRM, supply chain platforms).
• Agentic AI shifts from experimental to operational.

Leaders feel they must decide which decisions can be delegated to AI agents, which require human review, and should must remain human-led.

Trend 2: employees will ask for more training and AI is okay

Most employees say the pace of technology change in their roles is sustainable, and that they’re confident about keeping up with new tools.

Twice as many employees say they would embrace, not resist, greater use of AI in the workplace, seeing the technology as a way to remove repetitive tasks and learn new skills. This aligns with findings in research by KPMG.

Executives expect a significant re-skilling requirement from their employees, so leaders should anticipate that at least half their workforce will need some form of re-skilling by the end of 2026, thanks to AI automation. Other surveys concur with IBM, and state the skills needed most are problem-solving, creativity, and innovation.

Employees say they are willing to change employers to access better training opportunities, meaning skills development now plays a direct role reducing employee churn.

Trend 3: customers will hold data policies to account

The executives surveyed agreed that consumer trust in a brand’s use of AI will define the success of new products and services. Consumers are willing to tolerate occasional errors, but not opacity.

Customers want explanations of how their data is used, knowledge of when AI is involved in interactions with them, and simple ways to opt in or out. The studies by Deloitte and KPMG (see above) reinforce this picture.

Implications for leaders include treating transparency as a product feature and selecting models that support explainability.

Trend 4: AI and cloud will need local provision

AI sovereignty—an organisation’s ability to control and govern its AI systems, data, and infrastructure—has moved to the centre of resilience planning. Almost all executives surveyed said they will factor AI sovereignty into their 2026 strategy.

In the light of concerns about data residency and cloud jurisdiction, leaders are rethinking where models run and where data lives. Studies from UK and European IT leaders show rising concern about over-reliance on foreign (read, ‘US-based’ cloud services in the latter case).

Advisory firm Accenture also urges leaders [PDF] to develop sovereign AI strategies that prioritise control, transparency, and choice.

Key takeaways include the need for portable AI platforms, monitoring for data compliance, and a heavy emphasis on the physical location of data.

AI resilience is ultimately about continuity and transparency. It requires ensuring the organisation can adapt and operate openly, even when the global technological and geopolitical landscapes shift.

Trend 5: planning on quantum advantage

The report’s findings say quantum is moving towards experimentation in the near term. IBM’s own research on quantum readiness (in line with its monetisation of quantum services) suggests that early quantum advantage is likely in targeted domains such as optimisation and materials science.

The report urges the identification of small numbers of high-impact quantum uses in the enterprise, and the joining of ecosystems early. “Identify big bets to win with emerging technologies, including quantum, and partner on innovation to share costs,” the report states.

(Image source: “California Perfect” by moonjazz is licensed under CC BY-SA 2.0.)

See also: How the MCP spec update boosts security as infrastructure scales

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