The US tech stock market tanked during the month of July due to a frenzied sell off in Asian markets of chips and memory stock. That dragged down big chip makers like TMSC and Micron and saw the likes of Google and Meta forced to make minor sell-offs to maintain their AI and compute spend. Bloomberg came to the conclusion that the dumping of US stocks would inevitably make it harder for companies to justify AI spend. So will the market have a knock-on effect on corporate investment?
According to Forrester’s latest planning guide report, more than 80% of business leaders expect to increase budgetary spend in 2027 but they’re also under pressure to “deliver value, modernize for AI, govern at speed, and maintain trust — all amid persistent volatility and budget scrutiny”. Those businesses are already committed to significant investment and should not seek to pause spend, however. The better response is to become more disciplined about where that money is being spent, what business outcome it supports and whether the organisation has the governance in place to scale that investment responsibly.
Steering investment
Volatility is a useful reminder that technology budgets should not be driven by hype or fear of missing out and gone are the days when investment was dictated by going for the ‘safe’ behemoth in the market. Instead, spend should be tied to value, risk reduction, productivity and competitive advantage.
For smaller organisations, that might mean prioritising a small number of practical initiatives that improve security, automation or operational efficiency. For mid-market firms, it may mean rationalising platforms, improving adoption of existing tools and creating clearer ownership around AI use cases. For larger enterprises, the focus should be on reducing complexity, improving governance and making sure large-scale infrastructure, cloud and AI investments are measurable.
The key is not to stop investing, but to invest with more intent. In the current environment, leaders need to ask: does this technology help us serve clients better, operate more efficiently, reduce risk or create measurable growth? If the answer is not clear, it should be challenged.
Reducing exposure
Forrester advises that organisations should also seek to rationalise and reduce their exposure by getting rid of AI initiatives that lack governance, clear ownership, success criteria or a defined path to scale and that’s sound advice. Such AI initiatives are unlikely to deliver sustainable value. In many cases, they create more noise, cost and risk than benefit.
That does not necessarily mean every organisation needs a full technology budget reset, but it does mean budgets need to be reviewed with more discipline. Rather than asking “how much are we spending on AI?”, leaders should ask “which AI investments are connected to a real business outcome, who owns them, how are we measuring success and can they scale beyond a pilot?”
There is still a lot of experimentation happening, which is necessary, but that experimentation needs boundaries. Organisations should be prepared to stop projects that are duplicative, poorly governed or disconnected from business priorities. At the same time, they should protect funding for AI initiatives that improve productivity, strengthen customer experience, enhance security or help the business make better decisions.
Where to focus spend
There is an important distinction to be made between cutting spend and redirecting spend. The opportunity these businesses now have is to take budget away from low-value activity and reinvest it in the platforms, data, governance and skills that allow AI to move from experimentation into meaningful operational impact.
I’d go one step further than Forrester though and advise that the organisation ditch fragmented pilots, duplicated platforms, underused tools, unmanaged cloud consumption and technology projects that cannot clearly explain the value they are creating. Also, do challenge any investment that adds complexity without improving resilience, productivity or customer outcomes.
It’s important not to throw the baby out with the bathwater. Foundational elements that contribute to efficiency, security and scalability should be priortised, so that includes cyber security, data management, cloud optimisation, modern workplace transformation, automation, AI governance and the platforms that give leaders visibility and control over their technology estate.
An area to strongly protect is spend optimisation. In a more volatile market, organisations need a clearer understanding of what they already own, what they actually use and where waste exists. That visibility often creates the funding needed for innovation. In other words, optimisation is not just about cutting cost, it is about freeing up budget to invest in the areas that matter most. Spend optimisation services can help here.
Four key areas to focus on
Internally, investment should be directed at four main areas, beginning with AI governance and adoption. The winners will be those organisations that can move beyond experimentation and embed AI safely into real workflows. That means clear policies, business ownership, success measures, data controls and a realistic view of adoption. AI only creates value when people use it effectively and when the organisation understands how to manage the risk around it and that takes guard rails.
Secondly, data and visibility. Many businesses want to move quickly with AI but do not yet have the data quality, knowledge management or operational visibility to support it. Leaders are recognising that AI readiness starts with the basics, clean data, accessible information, integrated systems and the ability to measure outcomes.
Then the third area to consider is cyber resilience. As technology environments become more distributed and AI introduces new behaviours, organisations need stronger controls, better identity management, improved visibility and a more proactive approach to risk. Security is no longer a separate technology conversation, it is central to business resilience.
And finally, cost optimisation and platform rationalisation. This is especially important as cloud, software, SaaS and AI consumption increase. The businesses that perform best will be those that can control spend, remove duplication, improve utilisation and then reinvest savings into higher-value transformation.
Taking stock and aligning efforts
Adopting this form of strategic investment will also see a growing need for closer alignment between IT, finance, procurement, security and business leadership. Technology investment can no longer sit in isolation. The most effective organisations are creating cross-functional ownership models, where investment decisions are connected to business strategy from the outset.
Nobody has a crystal ball and AI stock trajectories will no doubt continue to fluctuate but what is certain is that the organisations that navigate 2027 best won’t be the ones that spend more; they’ll be the ones that spend more intelligently.AI and technology volatility should not push leaders into paralysis or rash decisions. It should push them towards greater discipline. So the focus has to be on measurable outcomes, stronger governance and a clearer understanding of where technology genuinely improves the business.
