Stop Chasing AI Hype and Start Building Strategy

Jon Burghart at AnywhereNow explores how customer service leaders can move beyond the hype to build a clear, strategy-led approach to AI.

AI is often marketed as a transformative solution for customer service, just switch it on, and your contact centre is expected to evolve into a sleek, intelligent operation. The promise? Instant support, hyper-personalised experiences, and seamless handovers, all delivered effortlessly.

Let’s cut through the noise: it doesn’t work like that.

Spending enough time in the trenches and the boardroom, you realise that AI isn’t a plug-and-play solution. It’s not a feature set. It’s a transformation.

And like any meaningful transformation, it demands more than enthusiasm and software licenses. It requires strategy and executive buy-in.

Customer service and support (CSS) leaders are under constant pressure to lead AI initiatives and prove their value.

According to the 2025 Gartner Business Buyer Survey, 93% of service and support technology buyers emphasised the importance of AI capabilities in their tech investments.

That’s a staggering number. But what’s the most worrying is how many of those investments are being made without a clear strategic foundation.

When talking to executives, we always ask: What problems are you solving with AI? Because too often, the real issue isn’t the tech, its misaligned goals, vague metrics, and disconnected teams. If we don’t start with clarity, we’re setting ourselves up to fail.

Four Pillars of Successful AI Implementation

To roll out AI effectively, the Gartner Playbook for Successful AI Implementation in Service and Support recommends focusing on four foundational pillars. It was interesting to see that only one of these pillars is technology related.

1. Leadership Alignment: Start Your Strategy at the Top

AI initiatives fall apart when leaders aren’t aligned. This is why leadership involvement is critical from day one. Stakeholders must agree on shared objectives and define what success looks like, whether it’s cost reduction, improved customer experience, agent empowerment, or all three.

Scenario planning and ROI modeling help align expectations and build confidence. Regular steering committee meetings with cross-functional leaders maintain momentum, ensure accountability, and allow for course correction as the project evolves.

2. Technology Strategy: Don’t Just Buy – Build with Purpose

Once we know what we’re solving, the business can build a roadmap. Not a feature checklist, but a strategic plan.

Leaders should identify high-impact use cases that solve real problems, assess build-versus-buy options, and prioritise quick wins that lay the foundation for more advanced capabilities.

Executives shouldn’t be chasing shiny objects. They should be solving real problems with the right tools, at the right time, in the right way.

3. Data Readiness: Trust Begins with Clean Data

AI is only as good as the data behind it. We’ve all heard about AI hallucinations and misinformation. That’s why data hygiene is a strategic imperative.

Therefore, my advice before you launch anything is to audit data architecture, refresh knowledge programs, and establish governance for ongoing quality.

This isn’t just technical diligence; it’s about trust. If your AI can’t be trusted, your customers won’t stick around.

4. People Preparedness: Culture Is the Real Catalyst

AI can be intimidating. I’ve seen teams resist it because they fear being replaced. That’s why we encourage our customers to invest in change management and training early. When agents understand how AI supports them, not replace them, adoption skyrockets.

This is more than a tech rollout. It’s a cultural shift. And if your people aren’t ready, your strategy won’t resonate, and you won’t realise the business outcomes the Board planned at the outset.

Start Small, Win Fast, Think Big

Being strategic and having a vision doesn’t mean going slowly. I always encourage companies to start with low-risk, high-reward capabilities that deliver immediate value.

Summarisation tools, intelligent routing, knowledge assist; these aren’t just tactical wins. They’re proof points. They build confidence and momentum quickly.

Furthermore, these capabilities don’t require massive infrastructure changes or deep technical expertise. They’re strategic steppingstones toward deeper transformation and more advanced customer service and AI integration.

AI Is a Spectrum, Not a Destination

AI isn’t binary. It’s a spectrum, from simple automation to predictive intelligence. You don’t need to leap to the endgame.

Start where you are, learn fast, and build forward towards more sophisticated solutions. The companies winning with AI aren’t the ones with the flashiest tech. They’re the ones with the clearest strategy and vision, strongest executive alignment, and the courage to lead with purpose.

For more information about AnywhereNow - visit the AnywhereNow Website

Call Centre Helper is not responsible for the content of these guest blog posts. The opinions expressed in this article are those of the author, and do not necessarily reflect those of Call Centre Helper.

Author: AnywhereNow
Reviewed by: Rachael Trickey