Now is not the perfect time for AI. It never will be.

Technology executives are doing what they do best: comparing vendors, assessing readiness, modelling risks, building business cases and running AI pilots. The problem is that while they deliberate, their contact centre staff work harder with aging tools, and customers receive slower, less personalised service than the competition.

The fact is: you can’t analyse your way through this one.

And who do you bet on when everyone claims to have the answer?

These are the issues keeping tech leaders up at night. As one CIO told us: “I need AI to be strategic, not experimental. But how can I commit when everything changes every month?”

The uncomfortable truth: unless a competitor, colleague or the market delivers a wake-up call that decides for you, the perfect moment will never arrive.

The executives making progress are the ones who’ve accepted that the opportunity cost of waiting for ideal circumstances now exceeds the risk of imperfect action.

The velocity of change makes waiting pointless

In the three months it takes to complete a typical readiness assessment, major platforms will have released hundreds of cloud and AI updates. By the time you’ve assessed vendors, capabilities and business cases, the entire market has shifted.

One financial services client captured this perfectly. Last year, their directive was explicit: “Don’t mention AI in any proposals – it won’t get approved, too risky.” Eight months later, they signed off on an urgent AI voice assistant project. Competitors had moved, customer expectations had evolved and suddenly the risk of inaction outweighed previous concerns.

A healthcare provider laid out their reality: a growing population, increasingly complex services and zero additional headcount approved for the foreseeable future. They didn’t want to adopt AI – they had no choice. Without it, they’d be overwhelmed within 24 months.

Too many choices, not enough decisions

Every major platform now offers AI capabilities. Every vendor has a compelling story. Every consultancy has a methodology. The result can be decision paralysis.

Successful organisations are realising that you don’t need to pick the perfect AI solution. You need to back the platforms you’ve already invested in and make them work harder.

This requires strategic thinking, not recklessness. The organisations seeing fast AI returns are the ones saying, “We’ve invested in these core platforms – now let’s unlock their AI potential.”

Moving beyond POCs to deliver real results

Government agencies aren’t known for moving fast on emerging technology. Yet one state government recently adopted a refreshing approach to innovation, where it stopped experimenting with proof of concepts and instead committed to full-scale projects. Proof of value is becoming the new proof of concept.

Their reasoning was compelling. By the time you’ve navigated privacy, security and governance requirements for an AI pilot, you’ve done 70% of the work needed for production deployment. The difference is that projects have committed resources, clear metrics and invested teams. POCs often end with applause but no action.

This shift in mindset – from experimentation to implementation – changes everything. It forces clarity on value, commitment to scale and most importantly, learning through doing rather than planning.

Your platforms are already AI-ready

While you’re evaluating standalone AI solutions, the enterprise platforms you’ve already invested in have been quietly building powerful AI capabilities. Major players such as Microsoft, ServiceNow and Genesys have poured billions into embedded AI that works within their ecosystems.

AI thrives on unified data and integrated workflows. When your customer service platform can access service management data, when your workflows can trigger across systems, when your data tells a complete story – that’s when AI delivers multiplied value, not isolated improvements.

This is why the collaboration between ServiceNow and Genesys is significant – their purpose-built integration creates the unified workspaces and shared data layers that make AI truly effective. As we recently explored, the real multiplier effect stems from reducing platform complexity and achieving true integration.

The organisations winning with AI recognised that their existing platform investments, when connected and working together, were already AI-ready. They’re making strategic bets on their core platforms rather than chasing every new AI solution.

Back your strategic bets, move fast and adapt

Start where you are. Use your existing platforms. Focus on integration over innovation. Set up projects, not POCs. Accept that imperfect action today beats perfect planning tomorrow.

The perfect moment to go big on AI will never arrive. But for organisations ready to back their platform investments and commit to real projects, the right time to start is now.