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FEATURE: INVESTMENTS

CIOs are under increasing pressure

with operational robustness? Three movements

KPIs fall into the category of low-cost experiments

2. Strengthen the core for resilience:

c. Transform – explore AI / data bets: 15 – 20 %

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24 to embrace AI-driven innovation

FEATURE: INVESTMENTS without compromising security, stability or cost-efficiency. Industry rather than the executive priority queue. experts share practical strategies

Before moving on to sophisticated designs, for balancing transformative technology investments with enterprise resilience in today’ s data-driven landscape. consolidate the foundation: architecture with multiple availability zones, immutable backups, end-to-end observability. Consider these layers as invisible capital – they rarely shine on the committee but they raise the innovation ceiling. An MLOps pipeline only generates ROI if it runs on reliable data and fail-safe infrastructure.

3. Manage a disciplined bimodal portfolio by distributing the budget across three buckets: a. Run – maintain essential operations: 50 – 60 % b. Grow – scale what already works: 20 – 30 %

Reevaluate this allocation every quarter. If a Transform project proves value, it migrates to Grow. If something in

Alexandre Bastos Borges, CIO, Pernambucanas new bets. Transparency in this“ bucket dance” minimises friction between innovation and support teams.

Run is automated and cheaper, it frees up resources for

Metrics that matter:

There’ s an inflection point in sight: data and AI drive new business models every day while the negative headlines fall on those who move forward without a solid foundation – ransomware attacks, cloud outages, GDPR violations.

How, then, does a CIO balance technological boldness

• Time-to-value of AI experiments( 90≤day proof)

• MTTR of the data platform( goal: < 30 min)

• Savings reinvestment ratio( how much of the efficiency gains goes back to Transform)

• Adoption rate of internal AI solutions( end-user engagement) complement each other:

Conclusion should focus on technology that creates genuine

1. Start with the strategic“ why”: Each investment needs to be linked to a measurable business objective – revenue growth, efficiency or risk reduction. Map corporate OKRs and associate them with clear indicators( avoided churn, gross margin, average recovery time). AI initiatives that don’ t demonstrate impact on these

Prioritising is, in practice, choosing where not to invest now. Without robust foundations, AI initiatives become expensive and risky bets. With stable operations, each new project converts into tangible value for the business. The CIO who masters the essentials creates the space to innovate with confidence – delivering customer benefits while keeping the company prepared for the unexpected. value and empowers people. At inDrive, we use AI for driver identity verification and fraud detection not because it’ s trendy but because safety is fundamental to our mission.

As a first step when considering new technology investments, CIOs should ask themselves two essential questions: does this investment align with our core values, and does it enhance human capabilities or simply replace them? Technology should never be a substitute for

How should CIOs prioritize technology investments to balance innovation with resilience in an increasingly AI- and datadriven enterprise landscape?

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Dr Roman Atachiants, Head of AI and Data Architecture, inDrive

Balancing innovation with resilience

Today, we face a critical challenge: how to drive innovation while building resilient, trustworthy systems. At inDrive, we’ ve learned that the most effective technology investments are those that push boundaries while reinforcing the foundations of trust, security and human connection.

1. Start with purpose The best AI investments solve real problems that users and businesses face. Rather than automating for efficiency’ s sake, companies businesses should focus on using it as a force multiplier that empowers their teams and helps them better serve their customers.

2. Build platforms that scale Companies should invest in unified data and AI platforms with strong governance from day one. This helps ensure compliance and enables your systems to adapt and grow as you scale without compromising security or putting user trust at risk. At inDrive, we’ re scaling our data and AI platform to enable real-time analytics and efficient MLOps while maintaining strict privacy controls( e. g. EU’ s GDPR, AI Act), regardless of local regulations.

Resilience comes from having robust foundations. So, establishing clear AI governance,

human judgement and empathy. Instead, www. intelligentcio. com internal codes of conduct and cross-functional teams that can experiment safely while scaling

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FEATURE: Security awareness training: A

INDUSTRIES: Fin. tech, Health. tech, Build. tech, Edu. tech, Gov. tech and Retail. tech

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