FEATURE: INVESTMENTS
what works is essential. This approach allows companies to innovate at pace while maintaining safeguards to protect what matters most.
3. Automate while keeping a human touch Not every process needs AI, and not every AI solution needs to be built in-house. At inDrive, we build when differentiation matters, like with our consumer experience and logistics algorithms, and buy when it accelerates time-to-value. This ensures resources are focused where they can create the most impact.
Some interactions require empathy and human judgement that AI cannot replicate, so companies should be intentional about where not to use AI. For example, at inDrive, our support agents handle complex customer enquiries that require emotional intelligence while AI chatbots handle more routine questions. This hybrid approach improves both operational efficiency and customer satisfaction.
Additionally, the most successful AI systems should improve, rather than replace, human decision-making. For example, our price recommendation system uses AI to suggest fair ride rates based on real-time data, but the app allows users to negotiate and ultimately choose the price they offer. This preserves human agency while leveraging the benefits of AI.
4. Foster an AI-first culture Technology investments must be paired with cultural transformation. Businesses should create environments where teams can experiment safely, learn from failures and scale what works. At inDrive, we promote AI literacy through training programmes and champion networks. We also invest in local talent and run companywide mentorship schemes. The most resilient organisations develop internal capabilities while staying connected to broader industry trends and best practices.
While changing the culture, companies should define success beyond traditional metrics. Yes, measure speed and operational efficiency, but also track trust indicators: user satisfaction, reduced friction and improved outcomes. For
example, at inDrive, we measure success by reduced cancellations, faster support resolution, higher customer satisfaction scores and increased conversion rates – metrics that reflect both innovation and user value.
5. The path forward There is a lot of hype around AI – some of it justified, some not. CIOs should prioritise investments that create a virtuous cycle: technology that enables innovation while building trust, systems that scale efficiently but remain human-led, and platforms that drive growth while reinforcing organisational values. The future belongs to organisations that can move fast without breaking things, and harness AI’ s potential while keeping human connection and fairness at the centre.
Igor Benincá, Head of AI, Indicium
As AI races from pilot projects to core business infrastructure, CIOs face a dangerous paradox. They are expected to lead Digital Transformation at breakneck speed while also ensuring enterprise systems remain secure, stable and aligned to longterm goals. Many will fail not because they lack ambition, but because they invest in AI the wrong way.
To balance innovation with resilience, CIOs need a smarter investment strategy that matches their organisation’ s stage of AI maturity. They must also build structures that allow experimentation without derailing enterprise stability.
Three phases of AI investment most companies must navigate
Across industries, companies are investing in AI across three distinct phases. Each phase reflects a different level of maturity and success depends on investing in the right priorities at the right time.
In the first phase, companies lay the foundation. Strategy takes centre stage. CIOs are spending on consulting, internal workshops and leadership alignment to define a vision for AI tied to business objectives. They’ re also identifying internal talent, conducting skills gap analyses and developing training or hiring plans. Modest investments in pilot platforms or proof-of-concept tools are common – not to build production systems but to explore possibilities and identify early roadblocks.
In the second phase, the focus shifts to discovering value and enabling adoption. CIOs are funding collaborative efforts to prioritise AI use cases through structured workshops and team integration. Organisations are rolling out tailored training for both
26 INTELLIGENTCIO LATAM www. intelligentcio. com