London – September 28, 2026 -- jaam automation has launched M. by jaam, an Agentic Work Management platform designed to close the gap between AI adoption and measurable business impact. The launch responds to McKinsey data showing 88% of organisations now use AI, yet only 7% have fully scaled it across operations.
Adoption outpaces execution, McKinsey data shows
McKinsey research cited by jaam found that while 80% of employees report AI has improved their individual productivity, only 37% of organisations see a positive impact on EBIT. jaam positions M. as a fix for this disconnect, arguing that fragmented processes across people, applications and systems prevent AI agents from understanding what needs to happen next in a workflow.
Context Engine links organisational knowledge to live work
At the core of M. is its Context Engine, which aggregates organisational knowledge, historical data and live work activity to give both people and AI agents visibility into how work moves through a business. The platform learns from decisions and outcomes over time, aiming to improve future automation without requiring organisations to overhaul existing processes.
Andrew Murphy, Chief Strategy Officer and Co-Founder at jaam automation, said business context has become a bottleneck in AI adoption, and that M. allows companies to build understanding through work already underway before expanding AI's responsibility as confidence grows.
Platform integrates with Microsoft's expanding agent ecosystem
M. is built to work with Microsoft Azure AI, Copilot and Power Platform, alongside custom-built applications and agents organisations have already deployed. Microsoft's own data shows active Microsoft 365 agents grew 15-fold over the past year, a trend jaam says creates a coordination problem for enterprises running multiple agent types across disparate systems.
Lucy Bourne, Co-Founder at Oaka Studio, a Microsoft partner growth and strategy consultancy, said successful AI adoption depends on combining people, systems and AI in a way that remains practical, secure and governed, rather than simply deploying new tools.
Five-stage model structures gradual AI handoff
M. moves organisations through five stages -- Analyse, Build, Work, Intelligence and Optimisation -- designed to progressively shift responsibility from people to AI agents as processes mature. Gartner identified "Universal Orchestration" as an emerging enterprise challenge in February 2026, reflecting growing demand for tools that coordinate AI agents, bots and people across vendors and systems.
jaam automation frames M. as part of a broader shift toward Agentic Work Management, allowing businesses to retain oversight while incrementally increasing automation across complex, multi-system processes.