[AI]AI business reality – what enterprise leaders need to know

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When JPMorgan Asset Management

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that AI spending accounted for two-thirds of US GDP growth in the first half of 2025, it wasn’t just a statistic – it was a signal. Enterprise leaders are making trillion-dollar bets on AI transformation, even as market observers debate whether we might be witnessing bubble-era exuberance.

The conversation reached a turning point recently when OpenAI CEO Sam Altman,

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’s Jeff Bezos, and Goldman Sachs CEO David Solomon each acknowledged market froth within days of each other. But here’s what matters for enterprise decision-makers: acknowledging overheated markets isn’t the same as dismissing AI’s

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.

Corporate AI investment reached US$252.3 billion in 2024, with private investment climbing 44.5%, according to

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. The question isn’t whether to invest in AI – it’s how to invest strategically while others – specifically, an organisation’s competitors – overspend on infrastructure and solutions that may never deliver returns.

What separates AI winners from the 95% who fail

An MIT study found that 95% of businesses invested in AI have failed to make money off the technology, according to

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. But that statistic masks a more important truth: 5% succeed – and they’re doing things fundamentally differently.

High-performing organisations are investing more in AI capabilities, with more than one-third committing over 20% of their digital budgets to AI technologies, a

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report shows. But they’re not just spending more – they’re spending smarter.

The McKinsey research reveals what separates winners from the pack. About three-quarters of high performers say their organisations are scaling or have scaled AI, compared with one-third of other organisations. The leaders share common characteristics: they push for transformative innovation rather than incremental improvements, redesign workflows around AI capabilities, and implement rigorous governance frameworks.

The infrastructure investment dilemma

Enterprise leaders face a genuine dilemma.

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’s Gemini Ultra

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US$191 million to train, while OpenAI’s GPT-4 required US$78 million in hardware costs alone. For most enterprises, building proprietary large language models isn’t viable – and that makes vendor selection and partnership strategy important.

Despite surging demand, CoreWeave slashed its 2025 capital expenditure guidance by up to 40%, citing delayed power infrastructure delivery. Oracle is “still waving off customers” due to capacity shortages, CEO Safra Catz confirmed, as per a

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report.

This creates risk and opportunity. Enterprises that diversify their AI infrastructure strategies – building relationships with multiple providers, validating alternative architectures, and stress-testing for supply constraints – position themselves better than those betting everything on a single hyperscaler.

Strategic AI investment in a frothy market

Goldman Sachs equity analyst Peter Oppenheimer

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that “unlike speculative companies of the early 2000s, today’s AI giants are delivering real profits. While AI stock prices have appreciated strongly, this has been matched by sustained earnings growth.”

The enterprise takeaway isn’t to avoid AI investment – it’s to avoid the mistakes that plague the 95% who see no returns:

Focus on specific use cases with measurable ROI: High performers are more than three times more likely than others to say their organisation intends to use AI to bring about transformative change to their businesses, data from

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shows. They’re not deploying AI for AI’s sake – they’re targeting specific business problems where AI delivers quantifiable value.

Invest in organisational readiness, not just technology: Having an agile product delivery organisation is

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with achieving value. Establishing robust talent strategies and implementing technology and data infrastructure show meaningful contributions to AI success.

Build governance frameworks now: The share of respondents reporting mitigation efforts for risks like personal and individual privacy, explainability, organisational reputation, and regulatory compliance

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since 2022. As regulations tighten globally, early governance investment becomes a competitive advantage.

Learning from market concentration

In late 2025, 30% of the US S&P 500 was held up by just five companies – the greatest concentration in half a century. For enterprises, this concentration creates dependencies worth managing.

The successful five percent diversify their AI vendors and their strategic approaches. They’re combining cloud-based AI services with edge computing, partnering with multiple model providers, and building internal capabilities for the workflows most important to competitive advantage.

The real AI investment strategy

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’s Sundar Pichai captured the nuance enterprises must navigate: “We can look back at the internet right now. There was clearly a lot of excess investment, but none of us would question whether the internet was profound. I expect AI to be the same.”

OpenAI’s ChatGPT has about 700 million weekly users, making it one of the fastest-growing consumer products in history. The enterprise challenge is deploying it effectively, leaving others waste billions on vanity projects.

The enterprises winning at AI share a common approach: they treat AI as a business transformation initiative, not a technology project. They establish clear success metrics before deployment. They invest in change management as much as infrastructure. And they maintain healthy scepticism about vendor promises and remain committed to the technology’s potential.

What this means for enterprise strategy

Whether we’re in an AI bubble matters less to enterprise leaders than building sustainable AI capabilities. The market will correct itself – it always does. But businesses that develop genuine AI competencies during this investment surge will emerge stronger regardless of market dynamics.

In 2024, the proportion of survey respondents reporting AI use by their organisations jumped to 78% from 55% in 2023, as per the

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data. AI adoption is accelerating, and enterprises that wait for perfect market conditions risk falling behind competitors building capabilities today.

The strategic imperative isn’t to predict when the bubble bursts – it’s to ensure your AI investments deliver measurable business value regardless of market sentiment. Focus on practical deployments, measurable outcomes, and organisational readiness. Let others chase inflated valuations while you build sustainable competitive advantage.

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