Leaders and laggards emerge. While the Artificial Intelligence (AI) revolution is still in its early innings, we are starting to see subtle signs of maturity; in particular, we are seeing a fading of overt hype around technology and increasing clarity on which subsectors of the technology industry AI will benefit, and which it will challenge. AI has emerged not just as an enabler of productivity, but also as a ruthless disrupter of the technology landscape. For every Nvidia or Microsoft riding the AI boom, there are others whose business models are being hollowed out by automation, service commoditisation, and shifting customer expectations. Two categories that look particularly exposed are: i) enterprise software vendors built on premium pricing; and ii) IT services firms reliant on labour-intensive delivery models.
The software squeeze. For enterprise software, customer relationship management (CRM) and creative software suites are being progressively disrupted. Generative AI can now automate lead scoring, customer outreach, and even content generation at a fraction of legacy costs. The premium charged by incumbent platforms for vast CRM suites looks increasingly unsustainable. AI-native competitors will cherry-pick functions, offering leaner and cheaper systems. The incumbents’ high subscription fees will come under mounting scrutiny. For creative software, the challenge is arguably greater; generative AI tools that are currently available at little or no cost can produce images, videos, and marketing collateral that, while not perfect, are good enough for a wide swath of commercial use cases. Their pricing power is eroding as the perception of creative tools shifts from premium craftsmanship to commoditised output.
IT services unravel. Many IT services giants have built their fortunes on providing armies of engineers to manage clients’ IT estates. Their model hinges on scale and wage arbitrage. However, AI is beginning to automate code generation, testing, and even system integration. Tasks that once required large offshore teams are now increasingly achievable with smaller groups supported by AI co-pilots. While demand for complex, bespoke projects will likely endure, the bulk of “business as usual” IT spend is at risk in a world where machines are doing more of the grunt work.
Implications for investors. The losers of the AI revolution share common traits: dependence on pricing power that is now eroding, exposure to commoditisable functions, and limited ability to differentiate beyond incremental integration of AI. Software categories most at risk include:No longer a tide that lifts all boats. Investors should be wary of companies whose core value rests on labour scale, premium subscription bundles, or monopolisation of creative workflows. Defensive integration of AI (i.e. bolting it onto legacy products) also rarely offsets the structural erosion of pricing power. The more resilient opportunities lie with firms that own proprietary data, provide mission-critical infrastructure, and embed AI at the platform level rather than the application tier. Accordingly, investors should approach traditional enterprise software and IT services with some healthy scepticism and instead tilt portfolio allocations towards firms positioned at the heart of the AI stack, where value creation – not value erosion – will be most pronounced.
Stick with AI winners. Big Tech continues to prove themselves as pioneers, natives, and winners in the race of AI adoption. Some notable examples include:
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