The retail sector in the UK is under significant pressure. Faced with an increase in National Insurance costs, higher living wages and a new packaging levy, margins are being squeezed.
Together, these changes will cost the industry a staggering £7 billion. In response, 70% of Chief Financial Officers are pessimistic about trading conditions for the year, with 67% feeling forced to raise prices to offset the increasing costs.
But what if this challenge also presents an opportunity?
In a sector ripe for transformation, these mounting pressures could offer retailers the chance to accelerate their shift towards AI and use this rapidly evolving technology to offset costs and shake up the sector.
Here, our Senior Industry Advisor, James Dennis, explores how retailers can turn this challenge into an opportunity by quickly overcoming common AI implementation barriers.
Beyond traditional cost-cutting with AI
As brands reshape their strategies to tackle these costs, it’s easy to turn to traditional, reactive solutions such as reducing marketing spend or workforces. However, these once-helpful tools no longer deliver the same impact in today’s retail sector.
Retailers need flexible, scalable solutions that help offset costs, reduce overheads and drive ongoing efficiencies. AI provides several opportunities to achieve this.
Able to automate routine tasks and optimise operations, this technology is transforming almost every industry. In retail, there are countless opportunities to improve systems and offset costs. Household names are already reporting successes, such as Klarna, which reduced marketing spend by 25% while increasing marketing activity, thanks to AI.
AI isn’t a silver bullet – but for retailers willing to modernise their foundations, it offers a powerful toolset for driving both resilience and relevance in a fast-changing market.
Overcoming challenges to AI adoption
However, with mounting pressures, retailers need to overcome implementation barriers at speed. While leaders are forging ahead, others still struggle with issues such as:
- Skills shortages and lack of AI confidence
Challenge: While AI is maturing rapidly, many tools are still evolving and are unfamiliar to non-technical teams. However, a lack of expertise remains a primary concern among leaders, stalling implementation and limiting the scale of AI projects in retail.
Solution: Invest in upskilling staff to build AI literacy across departments. Introduce scenario-based AI training, focused on retail use cases like dynamic pricing, demand forecasting or returns fraud detection – rather than abstract ML concepts. This not only increases efficiency but also empowers staff to use AI with confidence.
A capability build model can also be transformative. Bringing in external AI partners to deliver co-piloted programmes where delivery includes coaching your teams (not just handing over a finished solution), helps educate staff through osmosis. This allows you to leverage the skills and experience of tech-focused companies.
- Legacy systems and siloed data
Challenge: Many retailers still operate with fragmented legacy systems and siloed data. Without good quality, accessible data, AI is limited in how much impact it can make at an organisation.
Solution: Understand your current systems and processes and identify opportunities for modernisation, such as strategic upgrades to data systems or platforms.
Data mapping workshops can help identify which data sources are critical for your chosen AI use case, such as CRM and web analytics for personalisation projects. Meanwhile, a data virtualisation layer can help connect siloed systems quickly, enabling AI experimentation without full replatforming.
- Unclear goals or business case
Challenge: It is crucial to identify which problem you intend to solve with AI. By solving the ‘wrong’ problem, retailers risk wasted investments and projects lacking momentum.
Solution: Turn to technology and industry experts for support in identifying the most impactful use cases. These organisations recognise that a lot of the challenge lies in asking the right questions. Often, design thinking workshops help provide a tactical exercise in achieving this, reframing AI as a problem-solving tool through strategic questions such as “How might we reduce returns by 20%?”.
Prioritise use cases that impact operating expenses (OPEX) or earnings before interest and taxes (EBIT) rather than those that inflate vanity metrics such as personalisation uplift. Decide on those that help offset rising costs, accelerate growth and improve operations.
Building a smarter response
The £7 billion cost increase for retailers will be a challenge. However, with the right response, it could also be an opportunity. Rather than reactive cost-cutting approaches, successful brands will turn to more strategic, long-term improvements.
With the chance to optimise pricing, get a deeper understanding of the customer and streamline operations, AI brings retailers a solution that could align with cost reduction and business growth.
To learn more about how retailers can use AI to offset rising costs, download our latest e-book. Or, find out how we’re supporting brands with innovative solutions for retailers.