A CEO’s perspective on navigating the agentic AI landscape
When it comes to AI implementation, CMOs and CTOs shouldn’t let the hype overtake strategy, writes CX Lavender CEO Clint Bauer.
Artificial intelligence, in its newest iteration, has seized the business imagination yet again. This time, it’s not just generative, it’s agentic – promising to act autonomously on our behalf, execute complex tasks across systems, and potentially replace whole operational functions.
If that sounds breathless, that’s because much of the current discourse is exactly that. But here’s a hard-earned truth: when hype overtakes strategy, missteps follow.
Having spent two decades in the trenches of customer experience, I’ve seen technologies come and go. Each promised to upend the way we connect with customers. Some delivered. Others created more complexity than clarity.
Today, CMOs and CTOs stand at a similar crossroads. Do they lean into Agentic AI with urgency? Or pause to plot a course that’s not only technically sound, but experientially meaningful?
Five priorities for CMOs
From a marketing perspective, there’s an urgent need to refocus on what actually drives value in the customer experience: empathy, relevance, and emotional connection.
1. Prioritise emotional intelligence over automation
AI tools, particularly those capable of agentic behaviours, are being pitched as the next evolution of CX. But it’s important to distinguish utility from strategy. AI can enhance personalisation and scale, but it cannot replicate the subtleties of human emotion. At CX Lavender, we’ve found that the moments that matter most are still driven by human insight – AI might draft the response, but only people can judge the tone, right time to reassure, pause, or escalate.
2. Avoid confusing technology for brand identity
Agentic systems should be enablers of brand experience, not the experience itself. When AI becomes the focal point, it risks overshadowing the brand’s core identity. The best applications are those that feel native, not novel. Consider Spotify’s AI DJ, which enhances the experience without drawing attention to itself. In contrast, overly visible bots and systems can feel impersonal and intrusive.
3. Protect and evolve creativity, don’t outsource it to AI
Creative disciplines are equally affected. There’s concern that AI will erode originality, turning brand expression into a predictable pastiche of prompted content. But the real opportunity lies in evolving creativity, not replacing it. Prompt design, curation, and contextual judgment are now integral to modern creative roles. Creating from scratch has given way to steering, shaping, and refining AI outputs to remain on-brand and emotionally resonant.
4. Maintain transparency as a brand value
As we increasingly rely on AI, especially in customer-facing contexts, transparency and ethics become critical. The marketing function is now responsible not only for message and media but for how decisions are made within AI systems. Disclosing AI involvement and ensuring fairness in automated outputs are fast becoming non-negotiables in preserving brand trust.
5. Deliver AI experiences that are seamless, not showy
When customers notice your technology more than their experience, you’ve gone off track. Invisible AI is often the most effective, subtly enhancing interactions without making them feel robotic.
Five imperatives for CTOs
While marketers grapple with front-end relevance, technology leaders are addressing foundational realities.
1. Build strong infrastructure before visible features
Agentic AI requires more than just APIs and clever demos. It needs robust architecture: clean data, orchestrated workflows, and rigorous governance. A tier-one retailer we advised spent the bulk of their AI investment on systems integration rather than flashy LLMs. That back-end discipline enabled scalable value without performance compromise.
2. Design for constraints as much as capabilities
As agents start making decisions not just recommendations, the need for guardrails intensifies. The most effective agentic AI systems have clearly defined boundaries, fail-safes, and human-in-the-loop protocols. In one recent industry example, an AI-driven support system gained traction precisely because it had limited autonomy and clear escalation processes to human staff. It’s a reminder that constraint, not capability, is often the differentiator.
3. Prepare legacy systems for integration, not resistance
Rushing to deploy capabilities without foundational upgrades will only compound technical debt – and expose it in ways previously hidden. AI reveals fragility in systems thought to be stable. CTOs must prioritise interoperability and technical debt management.
4. Lead organisational change, not just tech upgrades
The success of any AI initiative is deeply cultural. Tools that change workflows must be introduced alongside support, training, and trust-building. Microsoft’s Copilot rollout is a standout example of this alignment, pairing technical deployment with behavioural change programs across the organisation.
5. Avoid vendor lock-in by maintaining ownership
Many large vendors are positioning themselves as essential AI gatekeepers. But proprietary platforms often come with hidden lock-in and limited agility. CTOs must scrutinise vendor models carefully. True transformation requires retaining control over data, models, and roadmaps. Look for partners who transfer capability, not just offer it.
Clint Bauer
What next?
Australia has an opportunity to lead in responsible AI deployment, not just consumption. That won’t happen if we simply follow Silicon Valley blindly. Our market nuances, regulatory environments, and customer expectations demand a more considered approach.
We don’t need to be the Lucky Country or the Lazy Country. We can be the Thoughtful Country – implementing technology not because it’s fashionable, but because it’s fit for purpose.
When implemented strategically, AI manages standardised processes so we can focus on differentiated experiences. It handles predictable interactions so we can address nuanced customer needs. It processes routine data so we can derive meaningful insights.
The market leaders of 2025 aren’t organisations blindly implementing every available AI tool. They’re those who strategically determined:
- Which customer interactions must remain human?
- Which processes suit AI augmentation?
- Which technologies align with our strategic objectives and values.
Technical sophistication alone doesn’t determine market leadership. The advantage belongs to those who apply technology thoughtfully to address real human needs.
Ignore arbitrary implementation timelines promoted by consultancies incentivised to create artificial urgency. Excellence in execution – not speed – is your competitive advantage.
As a CEO, I’m not betting on speed. I’m betting on excellence.
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