Article last updated 12 February 2026.
A conversation that has moved into the mainstream
AI is no longer a specialist topic. It is shaping how companies operate, how employees work, and how capital is being allocated. This shift reflects the fact that AI is already being applied in practical ways, rather than remaining a theoretical promise.
For investors, the challenge is to distinguish meaningful long-term change from the short-term noise that often accompanies technological leaps. The enthusiasm is understandable, but it does not automatically imply a bubble. Nor does it guarantee rapid, economy-wide productivity gains.
Why this acceleration feels different
While comparisons with the dotcom era surface frequently, today’s landscape rests on stronger foundations. Businesses are investing heavily in the infrastructure needed to support AI, including data centres, specialist chips and cloud capacity, because they are already seeing benefits from the technology. These commitments are not simply speculative bets on future potential; they reflect tangible, real-world use.
Crucially, the companies leading the field are well-established, profitable global businesses with the resources to continue investing through periods of volatility. This financial resilience provides a buffer that was largely absent in earlier cycles of excitement.
Strong performance does not make a bubble
An unusual feature of AI compared to other recent technological breakthroughs is the dominance of a handful of very large companies. Their influence on market indices is significant, and valuations must always be considered carefully. However, strong returns alone do not suggest that markets have disconnected from reality.
Many of these businesses are generating meaningful revenues from AI-enabled products and services. Demand is already visible and expanding. This is very different from past periods when companies rose on little more than promise, with limited evidence of commercial viability.
Not every business referencing AI will prove successful, and a degree of over-statement is inevitable. Selective, disciplined analysis remains essential.
Progress tends to build over time
History shows that even the most transformative technologies take time to embed. Electricity and computing both delivered profound benefits, but only after organisations redesigned processes, retrained people and embraced new ways of working.
AI is likely to follow a similar pattern. Early gains are clear across customer service, research, healthcare support and software development. Broader productivity improvements will depend on thoughtful planning, investment in skills and changes in organisational culture. Investors should expect progress, but in measured stages rather than in dramatic leaps.
Recognising risks without overstating them
Rapid innovation always brings uncertainty. The scale of current investment is substantial, and returns may take longer to emerge. Economic conditions could influence the pace of spending.
Regulation will also play an important role. Questions around data security, bias, responsible use and transparency are becoming central to public debate, and oversight is likely to increase. Businesses that do not prepare may face challenges.
Labour markets will continue to evolve as tasks become automated and new skills grow in importance. Historically, technological change has led to job evolution rather than sweeping job losses, but transition periods can still be disruptive.
Where opportunity may emerge
While attention focuses on the largest technology companies, value may also be found elsewhere. Businesses enabling AI through analytics, automation, data management and infrastructure could offer compelling long-term prospects.
Smaller and mid-sized companies are also worth watching. After a period of under performance relative to larger peers, their valuations look more appealing. As the global economy steadies and adoption broadens, this part of the market may regain momentum.
Geographically, opportunities may arise in regions less concentrated in mega cap firms. Europe, for example, is home to specialist software and data companies integrating AI to strengthen established business models.
Selectivity remains the guiding principle. Companies with strong balance sheets, proven capabilities and a clear, thoughtful approach to innovation are better positioned to deliver sustainable performance.
Taking a balanced view in a transformational decade
AI is already reshaping corporate behaviour, and its influence will continue to grow. Investors do not need to choose between optimism and caution. A balanced approach recognises both the potential and the challenges ahead.
Fundamentals still matter most: earnings strength, competitive advantage, disciplined capital allocation and adaptability. These qualities have supported long-term investment success for generations and remain just as relevant in this new era.
AI will evolve, surprise and disrupt. By keeping perspective and focusing on sustainable growth rather than short-term excitement, investors can position themselves thoughtfully for a technology likely to shape the decade ahead.
