#23 The Real Challenge of AI Adoption: Understanding the Problem Before Choosing the Solution

As AI continues to take center stage in business transformation, one thing has become painfully clear: too many companies jump to solutions before fully understanding their actual problems. And that’s where most AI initiatives go wrong.

Take a government client we spoke with recently. They receive 33,000 calls a year, each averaging 12 minutes. Naturally, their first instinct was: “We need a voicebot to handle this.” But is a voicebot today really the best solution here?

Expectation vs. Reality in AI Adoption

This is something we see time and time again. Businesses expect too much, too fast. AI is seen as a magic bullet, but reality is often more complex. The real challenge isn’t just about implementing AI; it’s about making the right strategic choices for AI. That requires asking the right questions upfront:

• Why are people calling in the first place?
• Which issues need automation, and which require a human touch?
• What are the real bottlenecks that AI can solve efficiently?

For our government client, 53% of these calls were informational—answers that were already available via internal and external systems. Instead of jumping straight to a voicebot, wouldn’t it make more sense to build a chatbot that pulls real-time data?

Or even better: integrate a process agent into their call system to automatically route requests, filter informational calls, and escalate only the complex cases to human agents?

The Skills Gap and Resource Shortages

Beyond strategic alignment, companies also face practical barriers to AI adoption. A recent report highlights that 60% of data and analytics professionals identify a lack of skills and resources as a primary challenge. The demand for AI expertise far exceeds supply, making it difficult for companies to find or train the right people.

Additionally, organizations must decide whether to build custom AI solutions or invest in off-the-shelf products. Both options come with challenges: custom AI can be expensive and complex, while generic solutions may not fit specific business needs. Budget constraints and unpredictable ROI only add to the hesitation.

AI Isn't One-Size-Fits-All

Another issue? The tech itself. Voice AI might work well in English, but in Belgium, most citizens speak Dutch or French. And the reality is: most voice models simply don’t perform as well in these languages as they do in English. Why invest heavily in a solution that isn’t mature enough to deliver the expected results?

This is the missing conversation in AI adoption. Too many organizations pick a technology first and then try to retrofit it into their workflows. Instead, they should start with the problem and work backwards to find the most effective and realistic AI-driven solution.

The Smarter Approach: AI as a Decision-Making Engine

The real power of AI isn’t just automation—it’s smart decision-making. Instead of blindly deploying a voicebot, a more effective approach could be:

1. Chatbot Integration – Handles informational requests quickly and efficiently.
2. Call Agent in the Phone System – Filters inquiries, automatically retrieving answers for simple cases.
3. Process Agent to Decide Next Steps – Determines whether an issue needs human intervention, reducing unnecessary escalations.
4. Automated Follow-Up – If a citizen calls about a permit, why not have AI send them an email with the relevant details immediately? It’s faster, more reliable, and more complete than a human taking notes.

This way, AI isn’t just about replacing humans—it’s about optimizing processes and making interactions more seamless.

AI Success Comes Down to Strategy, Not Just Technology

Businesses that win with AI aren’t necessarily those with the biggest budgets or the flashiest tools. They’re the ones that approach AI with a clear strategy, a deep understanding of their actual problems, and realistic expectations.

Are you, your business or someone around you talking about chatbots, share the following document (attached) with him/her. It will give them a better understanding what directions are possible!

So next time someone says, “Let’s build a chatbot” or “We need AI,” pause. Ask: What’s the real problem we’re solving? The answer might surprise you.