Post by Jaro Tomik

NEW ARTICLE! Co-written by William Oakley. A successful #AI adoption in 2026 requires clear business goals, strategy, and understanding of current capabilities rather than mere experimentation. #AgenticAI is not the future as it is already a reality of many businesses of different sizes, across many verticals, enabling rapid ROI and iterative value proof without perfect data. The importance of cultural change, process optimisation, integration strategies, accountability (CoE creation), and aligning KPIs with business value to fully realise AI benefits is still key in achieving success. • Prioritise business alignment: Successful AI adoption depends on understanding your business goals, strategies, innovation value, current capabilities, and data quality to unlock AI’s full power and impact. • Agentic AI is present and practical: Out-of-the-box agentic AI solutions for service management can deliver guaranteed ROI within months, support iterative adoption, and operate securely even with imperfect data. They transform workflows and enable automation with low IT dependency. The saved time is used to improve data quality and drive further automation. • Cultural and process change are critical: Strategically addressing cultural change, optimising processes, developing integration strategies, and adjusting KPIs to the business context are essential to avoid inefficiencies and maximise AI benefits. • AI adoption requires organisational readiness: Building teams, establishing automation centres of excellence, funding innovation via spend optimisation, and prioritising reducing digital friction are key to delivering frictionless enterprise service and managing shadow AI risks. • Extract business value from Agentic AI: Boost efficiency, improving decision-making, and creating better user experiences - we must also build trust in its outputs. That means understanding how the AI reaches its conclusions and ensuring its actions and responses are reliable and consistent, especially when it's used in business processes and connected to enterprise data and systems. These qualities are essential when choosing and evaluating the right AI tools. We are seeing a rise of AI-powered platforms that have governance and security built in, enabling you to do monitor the outputs and actions, and quickly spot and correct any hallucinations. Matt Dowling Heather Gilbank David Heaps Dan Bartram MIET Ignacio Castroverde Sanjay Chandra Neil Brady Gerd Brauner Cat Powell, Adam Crockford, Chuck Adkins Pascal Probst Cerie Paton Sarah Jones GSK Smeg Group Baloise CH NYSE Novuna Commerzbank AG Sheffield Hallam University Bupa Lucid Motors Cisco EY Gamma Vodafone CDW UK