Shahar Chen, CEO and Co-founder of Aquant, a company focused on delivering generative AI solutions to transform the service industry.
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As we approach 2025, the AI landscape is poised for a critical transformation. The past few years have been marked by rapid innovation, aggressive market hype and ambitious in-house AI development. However, the next phase will be characterized by pragmatism, driven by hard-earned lessons from early adopters.
Notably, a recent survey reveals that 74% of companies struggle to achieve and scale value from their AI initiatives, with approximately 70% of challenges stemming from people- and process-related issues. CIOs must be ready to adapt as the conversation around AI matures—from flashy buzzwords to real-world problem-solving.
From Building To Buying: A Strategic Shift
Building proprietary AI solutions has been a badge of innovation for many organizations, but the complexity of in-house development has caught up with them. Developing advanced AI systems can be exceedingly expensive, with costs potentially reaching up to $1 billion. By 2025, more enterprises will pivot toward buying established AI technologies rather than reinventing the wheel. This shift reflects a growing recognition of the costs, expertise and timelines involved in creating AI models from scratch.
For CIOs, the takeaway is clear: Evaluate vendors not just on technical specs but on proven impact. Can the technology integrate smoothly with existing systems? Does it address specific business challenges? Is it delivering ROI for its existing customers? A focus on outcomes will be essential.
Buzzwords Fade; Real Impact Endures
Autonomous "agents" are expected to take center stage in the artificial intelligence agenda next year, according to predictions from business executives and researchers interviewed at the Reuters NEXT conference in New York.
However, while terms like "agentic AI" continue to populate boardroom discussions, their influence will wane unless tied to tangible results. While conceptual jargon can inspire interest, the reality is that business leaders want AI solutions that solve pressing problems: closing learning gaps, improving decision-making and scaling operations efficiently.
CIOs should guide their teams toward conversations about performance metrics, deployment timelines and measurable ROI. In the coming years, success will be determined by the ability to connect AI initiatives directly to business value.
Overcoming Deployment Hurdles
Despite AI’s potential, many companies struggle with deployment. Challenges like fragmented data, skill shortages and lack of governance have stalled progress. To combat this, enterprises must adopt a more holistic approach—balancing technical innovation with operational readiness.
By championing cross-functional collaboration, CIOs can break down these barriers. Partnering with vendors that offer comprehensive support—ranging from initial implementation to ongoing optimization—will be a key success factor.
Building Long-Term Trust In AI
The maturation of AI will also bring a heightened emphasis on trust. As enterprises increasingly rely on AI for critical business processes, transparency, fairness and accountability will become nonnegotiable. Technologies that demonstrate ethical AI practices and compliance with regulatory standards will gain a competitive edge.
For CIOs, this means pushing beyond performance metrics to include trust-building measures like model explainability, bias monitoring and data privacy safeguards.
Looking Ahead
As AI evolves from hype to a sustainable business driver, CIOs must recalibrate their strategies. The winners in 2025 will be those who embrace ready-made solutions, insist on measurable impact and champion responsible AI deployment. By doing so, they’ll unlock the true potential of AI.
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{Author}Shahar Chen, Forbes Councils Member{/Author}
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