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How TMT companies use AI in sales to build a high-performing team

Authors

  • Ioannis Melas

    EY Studio+ Global Sales Transformation Solution Leader

  • Keith Stirton

    UK&I Customer and Growth Solutions Lead; Partner, Consulting, Ernst & Young LLP

15 minute read 04 Sep 2025
Related topics
Customer
AI
TMT

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. 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.

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.3

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.4

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.

How EY can help

This article explores 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: 

  1. 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. 
  2. 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.
  3. Upskilling sales teams to get the most out of AI, improving their ability to work with analytics and interpret and apply insights.

Each of the chapters below detail how AI can be implemented into the sales processes and the risk of not prioritising AI adoption. 

1

Chapter 1

Embedding AI into go-to-market processes

AI and sales automation can enhance the go-to-market process

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AI and sales automation can enhance the go-to-market process in multiple ways, allowing organisations to target, attract and convert more customers, providing sales, revenue and commercial leaders with increased insight to more accurately run their business, and removing non-revenue generating activity from sellers. 

 

To embed AI into the sales function, organisations typically follow one of the following adoption paths, each offering different trade-offs in speed, cost and control: 

  1. Custom-built solutions provide the highest level of flexibility and competitive differentiation, but require significant investment and longer development timelines.
  2. Native functionality within existing platforms enables faster implementation with lower upfront cost, though it may limit customisation and long-term adaptability.
  3. Use-case-specific applications allow firms to influence development and roadmap direction.

Choosing the right path depends on the organisation’s goals, capabilities and appetite for transformation.

2

Chapter 2

Getting data AI ready

Moving to a culture of structured data

As AI capabilities become more embedded in business decision-making, many organisations find the real challenge isn’t the lack of data, but a lack of accessibility, alignment and understanding. To help with this, organisations should: 

  • Think beyond numbers: valuable insights often lie in unstructured formats like customer emails, call transcripts or documents. Broadening the understanding of how data can be captured and processed helps build AI models that reflect the complexity of real-world customer behaviour. Equally important is understanding and complying with regulations on data usage, such as privacy laws and, in TMT, the Telecoms Security Act, to ensure AI initiatives manage risks effectively and maintain customer trust.
  • Prioritise connectivity and context: focus on tagging and linking data across platforms by implementing consistent metadata standards, using automated tagging tools and linking to data sets across platforms. Integrated, well-labelled data is far more valuable than isolated, clean datasets.
  • Build frontline data literacy: equip staff with the skills and tools to interpret data confidently and use it in daily decision-making.

Ultimately, being ready for AI means seeing data more broadly, connecting it more meaningfully and empowering people to use it effectively. 

3

Chapter 3

Rethinking the front- and middle-office operating model

A shift towards full cycle sales

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By streamlining and automating many tasks, AI allows sales teams to do more with fewer resources. This presents an opportunity to simplify the sales structure. Whilst many organisations are piloting AI through isolated use cases, often to cautiously test its impact, others are taking a bolder approach by rethinking their entire commercial operating model. These leading organisations see AI not just as a tool, but as a catalyst for structural change across the go-to-market effort.

 

One clear shift is the move towards full-cycle sales, where a single seller is accountable for the entire customer journey from initial prospecting and qualification through to closing, retention and expansion. This model reduces friction, eliminates redundant handoffs and places end-to-end ownership with the individual best positioned to influence outcomes: the seller.

 

Simultaneously, AI is automating manual, middle-office tasks, like reporting across marketing, sales and service operations, which previously required large support teams. Freeing up this capacity allows for the streamlining of operations and a laser focus on areas that will help drive growth.

 

Crucially, this operational streamlining creates space for sales managers to refocus on high-impact activities like coaching, development and performance enablement, rather than administrative oversight. AI should create capacity for leaders allowing them to reconnect with the front-line.

4

Chapter 4

Empowering salespeople to make the most of AI

Buyers could access more information and “self-serve” before needing to engage with a seller.

The role of the seller has been shifting well before AI was being deployed, as buyers could access more information and “self-serve” large parts of the sales process themselves, before needing to engage with a seller. Sellers have shifted from product experts to needing to become client and industry experts and guide stakeholders through their buying process. AI can deliver even more insights to the front line (in the form of customer, market, deal opportunity and engagement insight), giving sellers the support they need, provided they adopt the tools available to them and use them in a way that maximises their value.

The Future of Sales: How CSOs Can Transform Sales by 2030
increase in productivity gains was generated by sellers through AI implementation.

The technology, media and telecommunications executives surveyed for the recent global EY Responsible AI Pulse express some concern over their organisations’ capability to harness AI quickly. Half (51%) say resource constraints like talent, weak data infrastructure and competing priorities are a significant barrier to scaling AI initiatives within the sector.6

As organisations look to embed AI across the go-to-market process, they should not forget the importance of enabling their sellers to firstly, operate in a world where buyer and seller roles are ever changing and, secondly, have the skill set to utilise the tools to improve their performance.

The Future of Sales: How CSOs Can Transform Sales by 2030
times more likely to acquire customers for businesses using GenAI-assisted solution configurations.

It’s not just skills that are needed; sales professionals must also have a positive mindset towards AI, by clearly communicating how AI can be used to empower their role using concrete examples of productivity gains and enhanced customer engagement. Involving sales teams early on in the journey to AI implementation (selection, testing and feedback) can create a sense of ownership and co-creation, to help build a more positive outlook on the role AI can play. Interestingly, 38% of UK respondents to the EY Sentiment Index believe the benefits of AI outweigh the potential negatives, lower than the global average of 48%.7

The Future of Sales: How CSOs Can Transform Sales by 2030
of sellers have strong GenAI partnership skills.
The Future of Sales: How CSOs Can Transform Sales by 2030, Gartner.com
times more likely for sellers to meet quota if they have strong GenAI partnerships.

With thanks to contributor Tim Hillier, Director, Consulting, Ernst & Young LLP.


Summary

To meet the expectations of today’s highly informed and demanding customers, UK technology-led organisations should harness AI in sales to gain deep insight into products, customers and industry trends. Currently, only 44% of UK professionals use AI in their roles, highlighting significant untapped potential. As automation takes on more activities in the sales cycle, sales teams can accelerate go-to-market processes, streamline roles and reduce operational costs. Building trust in AI is critical, making it essential to foster a positive mindset and collaboration between humans and machines. By combining human expertise with AI-driven insights, UK organisations can boost performance and competitiveness.

How AI is reshaping the future of sales

Explore the new landscape for sales as AI reshapes customer expectations.

 

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    Authors

    • Ioannis Melas
      EY Studio+ Global Sales Transformation Solution Leader
    • Keith Stirton
      UK&I Customer and Growth Solutions Lead; Partner, Consulting, Ernst & Young LLP
    Related topics
    Customer
    AI
    TMT
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