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AI, AUTOMATION & POWER PLATFORM

How to convince your SME to adopt AI and Power Platform every day

A practical method for helping your SME adopt AI and Power Platform through a measurable pilot, proportionate governance and thoughtful user support.

By Fils Mery MONGO

Saying “we need to adopt AI” rarely convinces a team. Some colleagues hear an expensive trend; others hear a threat to their jobs or another tool to learn between urgent requests.

The strongest demonstration is not a long speech about the future. It is a visible improvement: a request that no longer disappears, a report prepared faster or an approval tracked without fifteen messages.

In this article

  1. Understand resistance
  2. Choose the first use case
  3. Build a pilot
  4. Measure value
  5. Protect data
  6. Support the team
  7. Move from pilot to adoption
Two SME colleagues review an AI-powered Power BI dashboard

Adoption becomes credible when the team sees a useful result and understands how it was achieved.

Why do teams resist?

Resistance is not always opposition to progress. It may reflect legitimate concerns: confidential data, unpredictable costs, AI errors, dependence on one person or a previous tool abandoned after three weeks.

Before proposing a solution, listen to painful tasks and perceived risks. A finance manager will not respond to the same argument as an administrative assistant or salesperson. Translate technology into their daily reality.

Discuss the problem before the tool

Instead of presenting Power Apps, Power Automate, Power BI and Copilot as a catalogue, begin with one process. For example: quote requests arrive through several channels, nobody knows their status and the weekly report requires two hours of copying into Excel.

Describe the current state using four figures: monthly volume, average duration, error rate and response time. These values form the baseline for evaluating the pilot.

Choose a convincing first use case

A good first case is frequent, reasonably standardised, visible and reversible. It should produce value without immediately exposing the company to a critical automated decision.

  • Centralise requests received through forms or email.
  • Automate document or expense approvals.
  • Send reminders and update status.
  • Create a dashboard from controlled data.
  • Summarise a non-sensitive document with human review.

Avoid beginning with a rare process full of exceptions or one that automatically makes financial, legal or employment decisions.

Build a limited pilot

Define a duration, small user group, owner and expected outcome. Map the trigger, steps, exceptions and data. Simplify before automating: a bad automated procedure is simply a bad procedure moving faster.

Power Automate can record a request, notify an owner, start an approval and preserve the decision. Microsoft supports human approval inside these workflows. Test rejection, absence, duplicates and incomplete data—not only the ideal path.

Measure value without inventing spectacular ROI

Compare before and after: handling time, errors, reopened items, response time and user satisfaction. Include licences, design, training and maintenance.

Value can also come from traceability, continuity and visibility. An SME does not need to claim “300% productivity” to justify a project. Saving a reliable thirty minutes every day on a recurring task may already fund useful improvement.

Build trust with proportionate governance

Microsoft recommends evolving governance with adoption maturity. At minimum, define roles, environments, approved connectors, solution owners and the support process.

Power Platform data policies control which connectors may share business data. Separate development, testing and production when a process becomes important. Use named accounts, least-privilege access and documentation that another person can follow.

Use AI without abandoning human judgement

Generative AI can summarise, classify, extract or draft, but it can also produce inaccurate information. Define permitted uses, prohibited data, review methods and accountability for the outcome.

Keep human validation for sensitive decisions. The NIST AI Risk Management Framework emphasises governing, mapping, measuring and managing risks throughout the lifecycle.

Support people, not only the solution

Explain what changes, what remains the same and how to get help. Train people using real tasks. Nominate a few champions and collect difficulties after launch.

My IT support experience taught me that a user asking a question is not blocking the project. They often reveal where our explanation or interface needs to improve. A one-page guide and short demonstration can be more useful than a three-hour training session.

Move from pilot to adoption

  1. Present outcomes and limitations honestly.
  2. Correct issues reported by users.
  3. Name the owner and document support.
  4. Confirm security, licences and capacity.
  5. Deploy gradually by team or process.
  6. Monitor real usage and retire what adds no value.
  7. Select the next case from business needs, not trends.

Key takeaway

To convince an SME, replace the general promise with local evidence: a well-chosen problem, a limited solution, protected data and a measured outcome. Adoption cannot be ordered; it is built with the people who will keep the solution alive. Let’s grow together.

“An SME rarely adopts technology because it is impressive. It adopts technology when it becomes useful, understandable and reliable every day.”

— Fils Mery MONGO

Let’s grow together

Which process should you improve first?

Let us discuss repetitive work, your data and the first measurable outcome AI or Power Platform could deliver.

Your satisfaction will make me happy

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