Jaam launches M. platform to scale AI across business

Jaam Automation has launched M., an AI platform for managing business processes across people, systems and AI. The launch comes as companies try to move from AI trials to broader operational use.

The product is designed to sit alongside software organisations already use, including Microsoft Azure AI, Copilot and Power Platform, as well as other business systems and custom applications. It is intended to help businesses understand how work is carried out before assigning more responsibility to AI tools.

Jaam is positioning M. around what it calls Agentic Work Management, a model focused on coordinating tasks and decisions across staff, software systems and AI agents. The premise is that many business processes do not sit within a single application or department, which can limit the usefulness of AI tools that lack broader operational context.

At the centre of the platform is a Context Engine, which combines information about an organisation, its knowledge, and work taking place in real time and over longer periods. The system is designed to map how work moves through a business and identify what should happen next.

M. can work with Jaam's own AI agents as well as agents developed by customers. The aim is to let organisations extend existing AI projects rather than replace them.

The launch comes against a backdrop of uneven returns from AI adoption. Jaam cited figures showing that 88% of organisations are using AI, but only 7% have fully scaled it across the business. It also pointed to McKinsey research showing that while 80% of employees said AI had improved their individual productivity, only 37% of organisations reported a positive effect on EBIT.

Those figures underline a common issue in corporate AI projects: strong interest and growing experimentation, but weaker evidence of broad financial impact. For suppliers in this market, the commercial case increasingly rests on connecting AI systems to everyday business processes rather than offering standalone tools.

Andrew Murphy, Chief Strategy Officer and Co-Founder at Jaam Automation, said: "Many businesses have adopted AI incredibly quickly but are struggling to make it work across the business. Every organisation has its own processes, systems, people and ways of doing things. If we're going to ask AI to take on more of that work, it needs to understand how the business actually works."

Murphy linked the problem to the way organisations store information across multiple teams and systems. He said businesses need a clearer operational picture before AI can take on a wider role in live processes.

He added: "Business context is a bottleneck in AI adoption, and that's the thinking behind M. by Jaam. Businesses can build that understanding through the work they're already doing, then introduce AI where it makes sense and give it more responsibility as confidence grows."

Microsoft links

Part of Jaam's strategy is to align the platform with Microsoft's software estate, where many large organisations already run collaboration, workflow and automation tools. This should make M. easier to deploy in environments that already use Microsoft services, while also allowing connections to other systems.

Jaam said the number of active Microsoft 365 agents has grown fifteen-fold over the past year, creating a need for companies to manage multiple AI tools alongside employees and existing workflows. It argues that M. offers a way to coordinate those elements without forcing businesses to rebuild systems from scratch.

Lucy Bourne, Co-Founder at Oaka Studio, said: "AI is changing how organisations work, however successful adoption is about more than introducing new technology. It's about bringing AI, people and existing systems together in a way that is practical, secure and governed. M. by Jaam provides a way to introduce AI progressively while maintaining visibility and control. Its alignment with the Microsoft ecosystem and ability to work with Microsoft Partners also provides a practical route for organisations already invested in Microsoft technologies to explore what agentic work can look like in practice."

Five stages

Jaam said organisations using M. can move through five stages: analyse, build, work, intelligence and optimisation. The stages begin with understanding processes and information flows, then move through live work support and monitoring before identifying where AI and automation can take on more tasks.

The broader market context is also shifting. Gartner has identified "Universal Orchestration" as an emerging challenge as organisations try to coordinate AI agents, bots and people across different systems and vendors. The trend reflects a wider move from isolated AI deployments towards integrated operational models.

For Jaam, M. is an attempt to address that integration problem by tying AI activity to the practical details of how work already gets done inside companies. As Murphy put it: "If we're going to ask AI to take on more of that work, it needs to understand how the business actually works."