The AI Investment Imbalance: Why 93% on Tech and 7% on People is a Strategic Mistake

The global AI investment landscape is at a crossroads. According to Deloitte, enterprises are allocating 93% of their AI budgets to technological development and just 7% to human-centric initiatives. While this imbalance reflects the allure of cutting-edge tools and infrastructure, it risks undermining long-term enterprise value creation. The data is clear: over-investing in AI's technical layer without addressing its human implications is a strategic misstep that could stifle innovation, erode trust, and exacerbate societal divides.

The Allure of the "Tech-First" Approach

The surge in AI investment is driven by the promise of automation, efficiency, and competitive differentiation. In 2024 alone, U.S. private AI investment hit $109.1 billion, with generative AI alone attracting $33.9 billion in funding-a 18.7% increase from 2023. This capital is flowing into foundational technologies like large language models, cloud infrastructure, and AI-driven analytics. The STOXX Global AI Infrastructure index, for instance, has risen 32% in 2025, reflecting investor confidence in these systems.

However, this "tech-first" strategy prioritizes short-term gains over sustainable growth. As noted in the 2025 AI Index Report, 76% of organizations now use AI, yet only 39% report enterprise-level EBIT impact. The gap between AI adoption and measurable value highlights a critical flaw: without aligning technology with human needs, enterprises risk deploying tools that fail to integrate into workflows, address ethical concerns, or foster employee buy-in.

The Risks of Neglecting Human-Centric AI

The 7% of AI budgets dedicated to people-centric initiatives-such as workforce training, ethical governance, and user-centric design-is alarmingly low. This imbalance creates three key risks:

1. Ethical and Regulatory Backlash: As AI systems grow more pervasive, public scrutiny intensifies. A 2025 McKinsey survey found that 77.6% of organizations have implemented ethical AI frameworks, but these efforts are often siloed and underfunded. Without robust governance, enterprises face reputational damage, legal penalties, and loss of consumer trust.

2. Workforce Resistance and Productivity Gaps: The EY Megatrends 2025 report estimates that human augmentation technologies (e.g., AI-powered training, brain-computer interfaces) could create a $1.39 trillion market by 2034. Yet, with only 7% of AI budgets allocated to these areas, companies are failing to equip employees with the skills and tools needed to collaborate with AI. This creates friction, reduces adoption rates, and exacerbates labor shortages.

3. Missed Opportunities for Innovation: Human-centric AI-systems designed to augment, rather than replace, human capabilities-is gaining traction. The Human-Centric Solutions for 2025 report notes that 92% of companies plan to increase AI investments, but the most successful adopters prioritize solutions that align with human values and agency. By neglecting this approach, enterprises miss opportunities to create AI that enhances creativity, empathy, and decision-making in sectors like healthcare, education, and customer service.

Rebalancing for Long-Term Value

To avoid these pitfalls, enterprises must adopt a dual-investment strategy:

• Scale Human-Centric AI: Allocate capital to tools that enhance human capabilities, such as AI-driven training platforms, explainable AI (XAI) for transparency, and collaborative robotics. The EY report highlights that $75 billion in funding for human augmentation technologies from 2023–2025 has already driven productivity gains in manufacturing and logistics.

• Embed Ethical Frameworks Early: As Deloitte emphasizes, 74% of organizations invested in AI and generative AI in the past year. However, ethical considerations must be integrated from the outset. This includes bias mitigation, data privacy, and stakeholder engagement-areas where the 7% budget is critically underutilized according to Deloitte.

• Foster Organizational Buy-In: The State of AI: Global Survey 2025 reveals that 76% of AI use cases are now purchased rather than built in-house. While off-the-shelf tools reduce costs, they also require cultural shifts. Investing in change management, leadership training, and cross-functional AI literacy is essential to ensure seamless adoption.

Conclusion

The 93/7 AI investment split is a symptom of a broader misalignment between technological ambition and human reality. While AI infrastructure will always be foundational, its true potential lies in its ability to augment human potential, not replace it. As the data shows, enterprises that prioritize both technical and human-centric investments will outperform peers in innovation, trust, and long-term resilience. The question is no longer whether AI is worth investing in-it's whether we're investing in the right way.