30 June 2025
James Clark, Data Protection, AI and Digital Regulation, partner at Spencer West LLP
Artificial intelligence (AI) has captured the world’s attention in recent years, and the IT network sector is no exception. With transformative potential for automation, predictive maintenance, network security, and more, AI promises much. As such, it has become a beacon for investment, and a watchword for companies when procuring all forms of technology services.
However, an emerging trend — often labeled as ‘AI-washing’ - has seen companies embellish or outright misrepresent their products as ‘AI-enabled’ or ‘featuring AI’ when, in reality, the underlying technology may not be all that smart - and something that, until very recently, would not have been badged as AI. This practice, reminiscent of greenwashing in an environmental context, is not harmless, and can have significant legal, reputational, and commercial consequences for companies operating in an increasingly competitive marketplace.
The allure and misuse of the AI label
For companies seeking to stand out in a crowded market, the temptation to ride the AI hype can be overwhelming. As there is no settled, technical definition of what constitutes ‘AI’, companies can take advantage of a linguistic grey-area to label conventional algorithms, or basic process automation, as AI. However, often these technologies have existed for many years and are not what the average person would understand as sophisticated AI.
Consequently, AI-washing can mislead stakeholders into believing they are investing in innovative technology that offers cutting-edge solutions to complex challenges. In an IT network context, these might include things like dynamic network management and real-time threat detection.
Legal risks
Regulatory bodies in various jurisdictions, such as the UK’s Advertising Standards Authority (ASA) and the U.S. Federal Trade Commission (FTC), are increasingly scrutinising marketing claims made by tech companies. When a company advertises a product as ‘AI-enabled’ without substantial backing technologies or clear definitions of what ‘AI’ entails, it may run afoul of misleading advertising laws.
In jurisdictions with robust consumer protection regulations, exaggerated or unsubstantiated claims can lead to legal actions for deceptive marketing or false advertising. For instance, if an IT network solution is marketed as capable of autonomously managing and securing complex infrastructures through AI but in practice only delivers basic rule-based alerts, customers might allege that they were misled.
In the realm of B2B sales, contractual agreements often hinge on the promised capabilities of a product. If a company's touted innovations fall short, business customers may take legal action for breach of contract.
For listed companies that trade their shares on public markets, there are also legal risks associated with misleading investors - in particular where AI capabilities are an important part of the company’s prospectus, the legal document that accompanies a company’s initial public offering (IPO).
Finally, an impending wave of AI specific regulation provides another reason for companies to think twice about advertising their products as AI-enabled. Laws such as the EU’s AI Act, which is coming online over the next 2 years, strictly regulate the development and use of certain AI systems. If a company holds its products out as being AI, it may inadvertently be inviting regulatory scrutiny under these emerging laws.
Reputational risks
Beyond the legal implications, AI-washing poses a threat to a company’s reputation. In the world of IT networks, technology credibility is paramount. Customers, partners, and investors expect companies to be transparent about their capabilities. When the discrepancy between marketed and actual performance comes to light, the resulting reputational damage can be severe.
In an industry driven by trust and technical reliability, once customers perceive that a vendor has engaged in deceptive practices, confidence in the company may erode rapidly. This is particularly pertinent in the IT networking sector, where system integrity, security, and performance are critical concerns. A network provider that misrepresents its capabilities risks not only losing current customers but also alienating prospective clients and strategic partners.
Additionally, industry peers and analysts are quick to note when a company uses AI as little more than a buzzword to stay competitive. Criticism in industry forums, social media, and reviews can amplify the negative sentiment, ultimately impacting brand image and market positioning. For companies that have invested heavily in their reputation, rebuilding trust can be a slow and costly process.
Commercial risks
While the allure of quick market traction is undeniable, the commercial risks associated with AI-washing must be carefully weighed. Initially, companies may experience a boost in demand and investor interest by aligning their products with the AI hype. However, these gains are often unsustainable if the product fails to deliver the promised functionality. A failure to innovate genuinely with AI can leave companies vulnerable to competitors who invest in authentic AI advancements. Over time, the market may begin to penalise the overhyped, creating a scenario where initial marketing gains give way to long-term commercial setbacks.
As customers become more conscious of the legal, ethical and operational risks associated with AI, they are beginning to implement additional procurement processes to assess and manage AI specific risks associated with their supply chain. By labeling a product or service as AI-enabled, a supplier may be opening itself up to enhanced customer scrutiny, and to having to complete additional assessments as part of the procurement or supplier onboarding processes.
From an internal perspective, misaligned product claims can also have repercussions. Sales and marketing teams that have built their strategies around exaggerated capabilities might find themselves unable to meet customer expectations. This can lead to internal disillusionment, demoralising teams and hindering efforts to achieve real technological breakthroughs. Additionally, investors may reconsider their positions if they perceive that the company’s technological claims were primarily designed for market hype rather than genuine innovation, potentially impacting future funding and growth opportunities.
Solutions
Given these challenges, technology suppliers should consider adopting a more measured approach to incorporating AI into their product literature and marketing strategies. It is imperative that the claims about AI capabilities are not only substantiated by tangible technological advancements but also communicated transparently to all stakeholders. This involves investing in robust internal audits of products, clearly defining what is meant by ‘AI’ within the business (perhaps by reference to emerging legal definitions, such as those in the AI Act) and ensuring that marketing materials accurately reflect the product’s true capabilities.
Conclusion
AI-washing is more than a mere marketing strategy — it is a risky shortcut that can jeopardise a company’s legal standing, brand reputation, and commercial success. Whilst the temptation to jump on the AI bandwagon and take advantage of the hype can be strong, in the longer term companies that are more circumspect may end up being more successful and, importantly, more trusted.
