Member report (Elsewhen): Building the Agentic Enterprise: AI Agents & Multi-Agent Systems
In today's enterprise, it’s common to have hundreds of software applications, most of which operate in silos, creating a tangled web of inefficiencies that hamper productivity.
AI-powered multi-agent systems (MAS) and AI agents address these inefficiencies by delivering three core advantages to enterprises: increased productivity, cost-efficiency, and adaptability. These capabilities form the foundation of what we call the agentic enterprise — an organisation where AI-driven systems collaborate seamlessly, adapt dynamically, and operate with a degree of independent reasoning.
By enabling real-time data flow and decision-making across previously isolated systems, these networks streamline workflows and reduce manual intervention, freeing up valuable time and resources. Their adaptability allows organisations to build solutions tailored to specific operational needs, reducing reliance on rigid, one-size-fits-all SaaS tools. By moving towards proprietary multi-agent systems and setting the groundwork for the agentic enterprise, businesses can build flexible, customised workflows that better align with their goals.
MAS are composed of AI agents, which range from basic task-specific tools to more advanced autonomous agents capable of agentic reasoning, planning, and adapting to changing conditions. While not all AI agents are necessarily fully autonomous, the integration of even basic agents can streamline operations and improve efficiency across complex workflows.
The adoption of AI agents is happening faster than you may think. According to a recent survey of over 1,300 professionals, 51% of companies already have AI agents in production, with 78% actively planning to implement them soon. Mid-sized companies (100–2000 employees) are leading the way, with 63% already deploying agents. Interestingly, this momentum isn’t confined to the tech sector; 90% of non-tech companies are using or planning to use agents, nearly matching the adoption rates of tech companies at 89%.
Elsewhere, with the arrival of multi-agent frameworks like OpenAI’s Swarm, LangGraph, and ReAct, enterprises can now bridge disconnected agents through intelligent, collaborative systems, creating a cohesive network that transforms decision-making and operational efficiency.
These frameworks are driving multi-agent systems to become increasingly agentic, meaning they are powered by autonomous agents capable of reasoning, planning, learning from past interactions and communicating with each other. This shift allows MAS to go beyond simple task coordination, fundamentally reshaping how software integrates within enterprise environments.
At the same time, Stripe now lets AI agents make controlled purchases using temporary virtual cards — another sign they’re moving from concept to reality.
Read Elsewhen's whitepaper, which outlines the strategic opportunities unlocked by AI agents and multi-agent systems and explore how they lay the foundation for the agentic enterprise.
techUK - Putting AI into Action
techUK’s Putting AI into Action campaign serves as a one stop shop for showcasing the opportunities and benefits of AI adoption across sectors and markets.
During this campaign, techUK will run a regular drumbeat of activity, including events, reports, and insights, to demonstrate some of the most significant opportunities for AI adoption in 2025, as well as working with key stakeholders to identify and address current barriers to adoption.
Visit our AI Adoption Hub to learn more, or find our latest activity below.
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Contact the team
Usman Ikhlaq
Usman Ikhlaq
Usman joined techUK in January 2024 as Programme Manager for Artificial Intelligence.
His role is to help techUK members of all sizes and across all sectors to adopt AI at scale. This includes identifying the barriers to adoption, considering solutions and how best to maximise AI's potential.
Prior to joining techUK, Usman worked as a policy, government affairs and public affairs professional in the advertising sector. He has also worked in sales and marketing and FinTech.
Usman is a graduate of the London School of Economics and Political Science (MSc), BPP Law School (GDL and LLB) and Queen Mary University of London (BA).
When he isn’t working, Usman enjoys spending time with his family and friends. He also has a keen interest in running, reading and travelling.
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