Reshaping Retail with AI: Valtech’s Rosanne Barendrecht

Generative AI (Gen AI) continues to revolutionise retail operations, with recent advancements boosting its use across the industry. 

From enhancing personalisation, to optimising processes, retailers are having to navigate challenges to harness the full potential of AI technologies. This is having to be done whilst ensuring that the ‘human element’ to operations are maintained. 

AI is reshaping how customers operate and interact with their consumers, but implementation challenges still remain. In this exclusive interview with AI Magazine, Strategy Partner at Valtech Rosanne Barendrecht explains how the strategic implementation of AI is needed to confront adoption challenges, whilst enhancing overall customer experience.

What retail operations stand to be most impacted by the adoption of AI technologies?

Opportunities range from aiding humans in their creative process, to delivering strategic insights as well as optimising and automating processes and enhancing the customer experience. 

Take product and supply chain, for example. AI can help predict sales, demand, and help determine optimal stock levels, aid product ideation and prototyping, and summarise feedback on products coming from stores, customer service and online. This can help product and merchandising teams improve back-end efficiency and customer service. 

In sales and customer experience, we’re seeing use cases around AI-powered search, hyper-personalisation at scale and AI-powered product recommendations take flight, allowing retailers to elevate customer experiences and drive customer loyalty.

Marketing and media are perhaps the areas where we see the most Gen AI being used today, from creating product descriptions, generating imagery and video, creating campaign recommendations and customer segments. And while there may be less buzz around traditional AI, there’s a lot of optimisation potential for marketing and media, for example through marketing mix modelling. 

We see a wealth of AI potential in organisational and operational processes. Think of optimising store employee onboarding through personalised training programs, or fraud detection.

How can retailers effectively leverage AI to enhance customer experiences and drive personalisation?

Over half of customers are actively seeking tailored products and services. Retailers, therefore, can leverage AI's power to cut through the noise and deliver personalised shopping experiences at scale.

AI can transform the digital customer journey through personalised interactions. We’ve seen the use of classic AI powered recommendation engines within eCommerce for years, but with the popularisation of Gen AI, the possibilities of truly personalised recommendations are even greater. Imagine a virtual shopping assistant suggesting the perfect outfit, providing customers with options they wouldn’t have otherwise considered. AI-powered conversational agents can do just that, by understanding customers' behaviours, purchases, questions, and preferences, guiding them through the shopping journey and suggesting new products. 

In the near future, I can see AI being used to generate on the spot, bespoke customer journeys. Beyond just recommending products and combinations, AI can truly guide the customer through the shopping journey, generating full pages based on what that customer needs in that moment of time. 

But personalisation doesn't stop online. In-store, AI is being used to help sales associates make more relevant product recommendations, tell the sales story the right way, and create more personal communication to their most valued customers at the drop of a hat. AI can also handle routine tasks such as KPI analysis, forecasting, ordering stock, and optimising product placement. This frees up sales associates' time, allowing them to prioritise the customer and provide their invaluable, expert advice. 

What are the key challenges retailers face in implementing AI solutions, and how can they overcome these hurdles?

We often find retailers are held back by unfocused efforts when implementing AI across an organisation. AI is rapidly evolving, making it difficult for retailers to keep up and have a clear vision on how best to leverage it. 

The key to overcoming this is putting business strategy, problems, and opportunities first. I would argue that retailers don’t need an AI strategy itself but need to explore where AI can accelerate their strategy for business growth and value. Starting small and embracing a structured trial and error approach can be a great way to get started and learn what works for your business. 

The second challenge is around data readiness. Many organisations fall into one of two potential traps: underestimating the need for strong data foundations to implement AI or allowing a lack of data maturity to keep them from exploring AI altogether. Data foundations and maturity are absolutely crucial to AI implementation, but a lack of data maturity doesn’t have to mean you can’t get started at all. We advise retailers to conduct small scale experiments and use these to identify exactly which parts of their data to focus on in the short term and ultimately build momentum for wider data maturity.

Organisational readiness is another recurring challenge, ranging from fear or a lack of employee trust in AI, to AI skills gaps, which contribute to slower adoption or issues in AI-powered outputs. Although there is not one clear answer for all organisations, it is crucial to keep in mind that change management is an integral part of adoption, as well as upskilling and hiring. For AI specific projects, I believe retailers need multi-disciplinary teams of their best people, who are eager to experiment and stimulate adoption.

AI isn’t perfect or without risk. Retail leaders should be careful not to overestimate its capabilities just yet. To ensure ethical and responsible use of AI that delivers real value, human input to instruct, evaluate, and approve outputs is crucial. 

How can retailers strike a balance between leveraging AI for efficiency and maintaining a human touch in customer interactions?

While AI can be leveraged for process optimisation and elevating customer experiences, it should not be used as a substitute for humans. A recent study found that while one-third of customers prefer AI-enabled interactions while exploring products or services, 45% would prefer options for both human and AI-enabled interactions at this stage. 

While AI is undoubtedly a growing resource in supporting the customer experience, at Valtech, we believe that AI should be used to enhance processes and experiences, not replace humans.

What role does data play in the development and deployment of AI strategies for retailers, and how can they ensure data privacy and security?

Data is the lifeline of AI. Without solid, clean data, there is no AI, so investing in a data strategy is critical. But beyond data readiness, retailers also need to consider how they can access, store and use data in a way that maintains customer trust and ensures privacy.  

Customers seek transparency in how their data is used and are generally willing to share it if they see the benefits. This requires retailers to clearly communicate with customers how they are using their data and how they are protecting it.  

The cookieless future, and changes in data protection regulation, present challenges here for retailers when it comes to accessing customer data. With less third-party data available, retailers should embrace zero-party sources, however many have not yet made the move.

It’s also important to note that it’s not just customer data that plays a key role. Company data is hugely valuable to many of the use cases I’ve outlined. However, businesses will need to ensure private company data is kept within secure environments to prevent outside access.

Looking ahead, what emerging AI technologies or trends should retailers be aware of to stay competitive and drive future growth?

First of all, it’s crucial to adopt an innovation mindset. The field is evolving at such a rapid pace that it’s easy to get left behind. So, in order to unlock real value retailers must be willing to experiment, learn, and even fail. 

Ensuring a solid data foundation and a flexible tech stack is crucial to this adaptability. By developing a composable strategy, which involves modular components that can be easily integrated and swapped out as needed, retailers can quickly and seamlessly adjust their AI strategy as new opportunities and challenges arise.

Retail leaders should also look beyond their industry for inspiration. Exploring how other industries are leveraging AI to innovate and improve customer experiences can help spark new ideas and drive unexpected breakthroughs.

It’s important for retailers to align every AI investment with clear business objectives that advance their overarching goals. By prioritising AI solutions that tackle specific customer, employee or business challenges, retailers can elevate experiences, optimise processes and uncover new opportunities for growth.

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