Contributed by EY.

How TMT companies can harness the power of AI to upskill sellers, better engage customers and boost go-to-market performance.

In brief

• AI is reshaping the go-to-market landscape, where speed is the new currency and buyer expectations of sellers are rapidly evolving.
• TMT organisations are actively exploring how AI can be deployed to enhance client experiences, empower sellers and drive operational efficiency.
• Sellers must become confident early adopters of AI and it’s up to organisations to enable, equip and support them through that shift.

The fast pace of innovation makes it harder than ever for technology, media and telecommunication organisations to stand out from the crowd. As customers become more educated and demanding, salespeople are under increasing pressure to engage at a deeper level. In the TMT space, broadband performance continues to drive UK consumer decisions when purchasing connectivity.

Decoding the digital home

Our Digital Home study revealed that consumers are sceptical about performance promises and 14% are prone to feeling overwhelmed by choice.1 This further strengthens the need for sellers to be experts in their customer base, with a deep understanding of the challenges their stakeholders are dealing with.

According to the Digital Home study, as the UK ranks above average for value-for-money perceptions driving their consumer behaviour, sellers face a tougher job at communicating value. By understanding the potential for AI to drive sales automation across many tasks, business functions are expected to get more value out of existing processes and teams and none more so than the sales function where there is pressure to generate growth and reduce the cost-of-sales.

Many organisations have rushed to adopt AI tools in pursuit of a competitive edge, often driven more by market speculation and fear of being left behind than by a strategic need. However, low adoption and high churn of these tools are being seen due to their failure to deliver tangible benefits. Without a clear, intentional AI strategy, organisations risk falling behind.

The rate of AI adoption

AI adoption is rapidly rising. In the EY Responsible AI Pulse survey, 72% of executives reported that AI has been integrated in most initiatives and 99% are at least in progress.2 Gartner research shows 20% of sellers gained 20% productivity due to AI adoption and Gen AI-assisted solutions make businesses 2.1 times more likely to win customers.

Whilst sales automation through AI is undoubtedly changing the way organisations go-to-market, its impact (and that of agentic AI) will vary by sales type. AI will play a bigger role in transactional environments, in some cases acting as the sole customer interface, whilst in highly complex, consultative sales, AI will work alongside sellers.

However, despite the growing use of AI, and some notable successes, there remains a degree of uncertainty over how to make the most of this technology and how to bring together humans and algorithms effectively. Responses to the 2025 EY Sentiment Index, which surveys consumer and business executives, show that sentiment towards AI remains cautious, with the UK scoring only 54 out of 100 – one of the lowest scores globally.

Such change brings risks many organisations are unprepared for. In the EY Responsible AI Pulse survey conducted in March-April 2025, 76% said they use or plan to use agentic AI within a year, yet only 56% knew the risks.5 Shifts in delivery models may disrupt traditional revenue streams, requiring careful planning for more unpredictable flows.

In our recent article here, we explore how sales leaders can utilise AI to inform, structure and upskill their teams to gain greater trust in data, and streamline the front and middle office.

What are the next steps to drive growth?

Recently, we held conversations with 15 business growth leaders in the UK, which revealed great enthusiasm for the potential of AI. This was also reflected in the EY AI Sentiment study, which highlighted that 82% of UK respondents are using AI, but adoption at organisational level is only 44%. Our conversations highlighted a variety of exciting use cases, as well as concerns about the impact on their operations, which might explain the gap between sentiment and use of AI that we have noticed in the UK. The effectiveness of AI in sales will be reliant on organisations being able to bridge that gap.

Whilst this may not be a new concept, the sheer pace at which AI in sales is enhancing capability (of both salespeople and customers) calls for a significant rethink of how to adapt the go-to-market approach to maximise the benefits.

To drive commercial growth through sales automation, leaders in sales should focus on three key actions:

• Operationalising AI into daily sales workflows, by working back from the seller and customer experience and attuning AI to each phase of the sales cycle.
• Building trust in AI through transparency and collaboration, involving salespeople in the introduction of AI apps (such as for use in customer engagement like chatbots or sales enablement to drive lead scoring). This drives better co-creation with the user and educates the workforce to see AI as a means to greater productivity.
• Upskilling sales teams to get the most out of AI, improving their ability to work with analytics and interpret and apply insights

For practical insights on how AI can be implemented into the sales processes and the risk of not prioritising AI adoption – read more here.

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