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thinkBIG
Cutting through the AI hype
Chapters
1 The AI journey every business is taking
Learn about AI, how businesses are using it, and what the latest trends show us
2 Understanding AI risks
Common AI risks and legal considerations, plus how to protect your business
3 Developing an implementation roadmap
Step-by-step implementation roadmap for effective AI adoption
4 Making AI part of everyday work
Leadership’s role in AI adoption and how to overcome staff hesitation
5 Measure, iterate and improve
Why AI adoption can never be ‘set and forget’
CASE STUDY:
Exaptec
Poornima Nathan is the CEO of Exaptec and has spent her career working at the intersection of enterprise technology, artificial intelligence and automation.
With a background in AI and robotics, she focuses on helping organisations in manufacturing, healthcare and education identify and deploy robotics solutions suited to their operating environments.
“Organisations can benefit from optimising their operations. Many businesses first consider off-the-shelf automation and AI products, which can be the right starting point. However, highly specialised workflows may require configured or targeted capabilities. The decision should account for integration, model usage, data storage, maintenance and change management, not purchase price alone."
“A tailored solution can combine domain capability with an organisation’s systems, business rules and exception pathways. For example, a hospital workflow should not stall because the approving nurse is on leave. If the solution is designed around the real process, it can identify the authorised alternative, route the request correctly and allow the automation or robot to proceed safely.”
Poornima says hesitation often surrounds AI adoption, making communication, training and staff involvement essential to the success of any new deployment.
“Existing staff hold valuable organisational knowledge. Reskilling them is often more effective than relying only on newly hired AI expertise. With role-specific training and support, people can learn to use AI systems effectively. Like any tool, AI’s value depends on how well it is designed, governed and used.”
When it comes to data security and governance, Poornima adds that both are critical throughout the AI lifecycle.
“With any AI solution, you need to know where your data is stored, how the model works, whether it is public or private, and which foundation model or technology sits behind it. You also need appropriate controls to protect confidential information. AI-specific regulation continues to evolve, while existing privacy, consumer and sector obligations already apply. Organisations therefore need strong governance and vendors capable of delivering secure, transparent implementations.”
This case study is featured in our thinkBIG report, Cutting through the AI hype: A practical guide to AI for SMEs.
Contributors
Ready to put AI to work in your business?
Whether you're exploring AI for the first time or looking to build on existing capabilities, RSM can help you identify opportunities, manage risks and develop a practical approach to AI adoption.
Ready to put AI to work in your business?
Whether you're exploring AI for the first time or looking to build on existing capabilities, RSM can help you identify opportunities, manage risks and develop a practical approach to AI adoption.