As 2026 approaches, profound changes are brewing in the fields of AI and enterprise technology. Predictions from leading industry solution providers, consultants, and thought leaders paint a picture full of opportunities and challenges. These predictions are not only about technology trends, but also point to how enterprises can redefine the value of data, infrastructure, and talent.
AI Readiness: From Slogan to Core Investment
After years of large-scale investment, enterprises have generally found that what truly hinders AI implementation is not model capability, but the readiness of data. Guy Adams, co-founder of DataOps.live, points out that by 2026, the AI readiness gap will become the primary reason for AI project failures and also the biggest driver of new spending. So-called AI-ready data refers to data that is trustworthy, governed, and aligned with specific use cases. Enterprises will no longer blindly chase AI pilots, but instead turn to capabilities such as automated pipeline orchestration, policy-as-code, continuous observability, and quality checks. These technical means can operationalize AI readiness, ensuring that models run at scale on a safe and reliable foundation.
Gartner regards DataOps as a strategic enabler of AI-ready data, and its core pillars—automation, orchestration, observability, testing, and governance—are becoming indispensable parts of the enterprise data lifecycle. In 2026, enterprises that embed DataOps practices into every aspect of their data will be the ones that can win the AI race.
AI Agents: The Rise of the Digital Workforce and Governance Challenges
Tyler Akidau, CEO of Redpanda Data, predicts that by 2027, the number of AI agents will exceed human employees for the first time—but only in the boldest, most operationally mature enterprises. In 2026, a few pioneers will approach this goal, while most enterprises, constrained by weak data infrastructure or conservative strategies, will remain at the chatbot level. Real AI agents will no longer have job titles or email addresses; instead, they will silently perform work through a governed data layer. This forces enterprises to establish new observability and audit models to track the activities of the digital workforce.
At the same time, as autonomous agents proliferate across data systems, the governance crisis will become the biggest headache for CEOs and CIOs. Traditional identity and access management (IAM) and role-based access control (RBAC) can no longer handle agents with short lifecycles that act dynamically across hundreds of services. Open frameworks and shared standards, such as MCP (Model Context Protocol) and A2A (Agent-to-Agent), will accelerate adoption and become the foundation of enterprise control planes. By the end of 2026, connectivity, governance, and context provisioning will become standard features of mainstream data platforms, with SQL coexisting alongside open protocols, enabling humans and machines to collaborate securely within the same governed data plane.## The Intermediary Role of Agents in Digital Ownership
Carlos Armada, Head of Product at name.com, points out that AI agents will become the new intermediaries of digital ownership. As agents take on more of the work of building and operating the web, domain and hosting providers will define how agents interact with the internet. When machines can act on behalf of humans, defining ownership, identity, and security becomes a core challenge. The industry needs to establish clear, transparent frameworks to build a foundation of trust for agent-driven activities, which will be the cornerstone of digital property management in the AI era.
Software Demise and Infrastructure Reshaping
Tiago Azevedo, CIO at OutSystems, describes a future of "Agent-as-a-Service." This market is expected to grow from $5.1 billion in 2024 to $47.1 billion by 2030. By 2026, employees will command a team of AI agents to orchestrate workflows across systems, rather than switching between multiple SaaS tabs. What truly drives business forward will be perceivable outcomes, not the software behind them. Agentic AI and AI-driven workloads require infrastructure with powerful computing capabilities (CPU/GPU/TPU), high-performance networks, scalable storage, and security governance measures. The enterprise AI data infrastructure market is expected to reach $7 trillion by 2030. Companies like Dell are strengthening their AI data platforms to help enterprises turn distributed data into more reliable AI outcomes.
At the same time, Azevedo believes agentic AI will re-humanize the enterprise. As tedious, repetitive tasks are taken over by agents, humans can focus on creativity, strategy, and emotional connection. Soft skills such as collaboration, adaptability, emotional intelligence, and judgment will become more valuable. In the HR field, for example, after agents handle the mundane aspects of onboarding and administration, each employee's productivity is expected to increase by 30%, and 23% of job roles will shift toward new positions that better leverage human talents.
Proving ROAI: From Quantity to Quality
Savinay Berry, Executive Vice President at OpenText, emphasizes that 2026 is the year to prove real AI return on investment (ROAI). Enterprises no longer need to show off the number of AI pilot projects. The real return is reflected in whether AI shortens release cycles, improves system availability, and speeds up fault recovery. Only when AI delivers measurable improvements in speed, quality, and stability can it become a trusted business advantage.
The Balance Between Flexibility and Control## The Balance of Flexibility and Control
Martin Bitzinger, Senior Vice President of Product Management at Mitel, believes that enterprise decision-makers have grown tired of chasing trendy technologies, and the key requirements for 2026 are flexibility and control. IDC views hybrid architecture as a mainstream strategy, combining on-premises deployment with cloud technologies to provide a safety net for business continuity and resilience. A true hybrid environment that can adapt to various workloads while maintaining unified governance will be the cornerstone of enterprise IT resilience.
Looking Ahead to 2026: Pragmatic Innovation
Taken together, the experts' predictions point to pragmatism as the defining theme of enterprise technology in 2026. AI readiness is no longer just a slogan but the baton guiding data investment; AI agents move from concept to production, forcing governance frameworks to evolve in tandem; infrastructure is being rebuilt for agentic AI, while the value of talent returns to its human essence. At the same time, enterprises will scrutinize every technology investment from a stricter ROI perspective. In the year ahead, organizations that can effectively combine data, agents, and human intelligence will gain a competitive edge.