How to Scale AI Across the Enterprise
Promise Akwaowo explains how to scale AI and measure real savings.
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AI can help businesses work faster, but proving its financial value is not always straightforward. From measuring savings to embedding automation into everyday processes, Promise Akwaowo explores what organisations need to get right to make AI work at scale. Ahead of his session at DTX + UCX London, Promise Akwaowo, AI and Automation Practitioner at Royal Mail Group, answers this Q&A explaining how organisations can scale their AI deployments to improve productivity and deliver financial benefits. Join Promise at DTX London on 14th October for his session titled From pilot to production: Making AI work at enterprise scale, where he will explain what it takes to move from AI experimentation to enterprise-wide execution.
Can you explain what you are talking about at DTX?
My individual session, “Where Did the Savings Go?”, explores turning automation time savings into real business value that finance can verify. I’m also joining “From Pilot to Production: Making AI Work at Enterprise Scale”, a panel exploring how organisations move beyond pilots into enterprise deployment.
What are the key benefits AI delivers to organisations today in terms of efficiency and cost?
Artificial intelligence (AI) can help teams process documents, find information and prepare responses faster, freeing people for tasks requiring judgement. The opportunity is to reduce backlogs, improve service and handle more demand with existing resources. Cost benefits depend on the task, output quality, adoption and the full cost of delivery.
Why do organisations not always immediately see the financial benefits from adopting AI?
Saving an hour does not automatically reduce expenditure. That hour may be spread across several people, absorbed by other tasks or spent checking outputs. Organisations also incur implementation and running costs. Financial benefits become clearer when released capacity leads to measurable changes, such as reduced overtime or avoided additional recruitment.
How can organisations scale their AI deployments to ensure they run enterprise-wide, and not in isolation?
Start with shared business priorities and involve operations, technology, finance and risk teams from the outset. Build reusable integrations, agreed data standards and clear ownership. Embed AI into everyday processes, train colleagues and monitor quality alongside cost. Expand in stages, using evidence from each deployment to guide the next investment.
What do you hope attendees will learn from your session at DTX
Across both sessions, I hope attendees learn how to move AI from isolated pilots into everyday operations and turn automation time savings into measurable business value. They should leave better equipped to plan enterprise deployment, support adoption, establish clear ownership, and agree benefits with finance that can be tracked and verified.
AI can help businesses work faster, but proving its financial value is not always straightforward. From measuring savings to embedding automation into everyday processes, Promise Akwaowo explores what organisations need to get right to make AI work at scale. Ahead of his session at DTX + UCX London, Promise Akwaowo, AI and Automation Practitioner at Royal Mail Group, answers this Q&A explaining how organisations can scale their AI deployments to improve productivity and deliver financial benefits. Join Promise at DTX London on 14th October for his session titled From pilot to production: Making AI work at enterprise scale, where he will explain what it takes to move from AI experimentation to enterprise-wide execution.
Can you explain what you are talking about at DTX?
My individual session, “Where Did the Savings Go?”, explores turning automation time savings into real business value that finance can verify. I’m also joining “From Pilot to Production: Making AI Work at Enterprise Scale”, a panel exploring how organisations move beyond pilots into enterprise deployment.
What are the key benefits AI delivers to organisations today in terms of efficiency and cost?
Artificial intelligence (AI) can help teams process documents, find information and prepare responses faster, freeing people for tasks requiring judgement. The opportunity is to reduce backlogs, improve service and handle more demand with existing resources. Cost benefits depend on the task, output quality, adoption and the full cost of delivery.
Patricia Cullen • Features Writer
Entrepreneur Staff
