Unlocking Opal: From boardroom approval to real results: The missing link

The technology is ready. The C-suite is bought in. So why do so many AI initiatives still struggle? At our exclusive breakfast, the answer became clear: success requires more than technology. 

There's a gap widening across organisations right now. Not between those who understand AI and those who don't. But between those who can execute on AI initiatives and those who can't. Last Thursday at Mortimer House, we brought together senior leaders from across industry sectors to tackle this execution challenge head-on. 

Susannah Streeter, award-winning BBC broadcaster and host of the EY-Microsoft Tech Directions podcast, opened the morning by cutting through the AI hype to focus on commercial reality. Her message was direct: organisations that lean into AI now will define the next decade. Those that wait will be playing catch-up. 

What followed proved even more valuable. A panel discussion brought together Emily Jewell and Jeremy Jenkin from Corinthia Hotels, Dipak Vaishi from Clarion Gaming, and our own John Prior and Zannah Ingraham to share real-world implementation stories. MSQ DX is at the forefront of Opal implementation, and we demonstrated our workflows in action to the audience. For Corinthia, we showcased how our agentic framework delivers enhanced personalisation at scale across their luxury hotel properties. For Clarion, we revealed a sophisticated 7-agent Opal workflow to power their job listings platform, demonstrating how multiple AI agents can work in concert to deliver complex, production-ready solutions. Then came intimate roundtable sessions where attendees wrestled with their specific challenges around content operations, personalisation, and AI adoption. 

The Gap Between Mandate and Reality 

A clear pattern emerged across both the panel and roundtables, regardless of sector or organisation size. C-suite buy-in for AI is strong. Translating that mandate into operational reality? That's where teams struggle. 

The challenge isn't technical. It's organisational. AI initiatives typically span multiple departments with different tools, ownership structures, and priorities. When content lives in one department and tools sit in another, who owns the AI strategy? Who's responsible for results? These questions surfaced repeatedly. 

Breaking down silos requires more than enthusiasm. It requires clear frameworks, governance, and measurement that everyone understands and buys into. 

Why Measurement Matters More Than You Think 

Throughout the morning, one principle kept resurfacing: you can't manage what you don't measure. 

But measurement isn't just about proving ROI. It's about building trust across silos and creating alignment on what success actually looks like. When you're asking teams to change how they work or adopt new tools, showing tangible impact makes all the difference. Demonstrating value, or identifying what's not working, creates the compelling business case that moves initiatives forward. 

Getting Personalisation Right 

One of the most engaging discussions centred on personalisation at scale. Customers expect you to understand their preferences and anticipate their needs. But walk too far, and helpful becomes creepy. 

The breakthrough comes from using agentic workflows that understand different customer personas and preferences, then deliver subtle content variations tailored to each person. Optimizely's Opal framework enables this through quality agents that maintain brand integrity whilst operating at scale. 

The distinction matters. Personalisation should feel like someone paying attention to your preferences, not tracking your every move. It's about responding to real human needs, not just mining data points. 

Building Trust Through Governance 

Maintaining trust whilst scaling AI outputs emerged as a critical challenge. Our Consulting Partner John Prior explained how Opal addresses this through quality controls built directly into workflows. Rather than having humans review every decision AI makes, separate quality agents assess outputs and alert supervisors only when issues arise. 

This approach enables organisations to operate at scale whilst maintaining brand standards. Using closed-loop models with your own data, rather than relying solely on external sources, provides both control and competitive advantage. 

One participant highlighted why this matters: AI systems sometimes generate references to pages that don't exist, making assumptions that seem logical but aren't accurate. Governance isn't optional. It's essential. 

Finding the Right Balance 

Success requires both top-level strategy and bottom-up autonomy. Pure experimentation doesn't scale. Pure mandates don't work. What does? Giving teams permission to experiment within clear frameworks, then scaling what proves viable. 

The skills gap remains real. Even with mandate and tools, organisations must ensure their teams can actually execute. As our Chief Client Officer Zannah Ingraham emphasised: "You need frameworks, governance, strategic alignment, and clear metrics so everyone understands the North Star." 

Keeping Humans at the Centre 

Despite coming from completely different sectors, attendees identified remarkably similar challenges. But there was also clear commitment to moving forward. These weren't conversations about whether to adopt AI. They were about how to do it properly. 

The consensus? The mechanisms will change, but human connection remains central. As digital experiences become more automated, the moments when people actually connect with brands become more valuable, not less. 

What This Means 

The commercial case for AI is clear. Success requires strategy, governance, measurement, and relentless focus on human value. 

Key principles emerged: 

• Start with business problems, not solutions 

• Use measurement to build trust across silos 

• Build governance into workflows from the start 

• Balance strategy with autonomy 

• Keep humans at the centre 

Continue the Conversation 

If these challenges resonate with your organisation, we'd love to continue the conversation. 

We're running tailored AI Transformation Workshops designed to help you move your initiatives forward with proven business value at the core. 

👉 Register your interest here 

MSQ DX is Optimizely's Strategic Global Partner and 2024 Customer Choice Partner. If you'd like to explore how Opal's agentic framework could solve challenges in your organisation, get in touch.