Silvio Palumbo is a managing director and partner at Boston Consulting Group (BCG) and a founder and global leader of Fabriq by BCG. He focuses on bringing an AI-enabled approach to multi-channel marketing platforms and solutions.
Awareness in Artificial intelligence (AI) has increased rapidly year-on-year. In fact, in both Sweden and the Netherlands interest in “artificial intelligence” on Google Search, has increased by 2X.1
Recent innovations have brought the world of AI to the masses. Not just as patrons of more optimised, relevant, and frictionless consumer experiences, but as hands-on users and adopters of AI solutions.
And retailers need to adapt now to succeed in the future. You’ve probably already had conversations with your teams on how AI can be an integral tool for driving efficiency, creativity, and profitability.
Beyond that, your customers have, more likely than not, read about the powers of generative AI — where AI is given a prompt and makes something new based on it — or even used it to create a novel output.
Here's how retailers can strive towards agility in embracing AI solutions:
- A focus on speed to market
- A new organisational model
- Evolving ways of working with collaboration and AI partners
Embrace speed to succeed with AI solutions
The democratisation of AI solutions — where AI is more readily available to everyone, even those without specialised knowledge — has widespread implications. Firstly, it has levelled the playing field in comprehension of, and access to, data science innovation.
Nimbleness and speed of adoption will become the defining criteria for success.
The second implication is that expectations from your customers have increased. They assume a high degree of efficiency, relevance, and optimisation across the entire purchase experience, from assortment to pricing. And they expect it to be privacy-safe and transparent.
Nimbleness and speed of adoption will become the defining criteria for success. Customers know what good looks like and expect retailers to deliver. For instance personalisation in all forms is now a standard consumers expect. AI solutions can help brands stay on top of these fast-moving consumer shopping trends.
Move towards a collaborative organisational model, with AI partners
A heightened comfort with ambiguity will be required as the pace of innovation increases. There’s no precedent to fall back on. The only way forward is through an organisational model that encourages rapid experimentation and leaning on collaborative working.
Collaborative working is not new, but AI is creating an additional hurdle through faster innovation cycles. Fast decision-making means embracing new corporate strategies. Your teams will not have time to build a business case, develop a prototype, test on a small scale, measure impact, and then roll the solution out. Halfway through that process the company board — and, more importantly, your customers — will be asking about the next wave of AI marvels making news.
So, instead you have to partner with external developers and experts in AI solutions to create an ecosystem of tools and applications that are custom-fit and tailored to your business. This allows for faster innovation cycles.
For example, a retailer might look to a conversational AI agent and focus on making it specific to its product assortment, descriptions, and brand guardrails.
A heightened comfort with ambiguity will be required as the pace of innovation increases.
This partner ecosystem, combined with your own organisational model, evenly distributes the innovation burden and allows focus on your brand’s own voice, as well as speed.
Speed drives direct and measurable financial outcomes, and sets apart retailers that can embrace it in their organisational model. It also drives other benefits, such as de-risking multi-year initiatives and investments through natural breakpoints or milestones.
Evolve ways of working for AI success in the new retail landscape
Brands need to move away from developing AI towards leveraging AI in a business context. This means solving an actual business problem, delivering a measurable outcome, and rewarding smaller successes.
This means a shift to a milestone-based approach to business outcomes.
Take, for example, a retailer wanting to improve personalised product recommendations using AI solutions, such as Recommendations AI on your ecommerce site. What’s typically a multi-year journey can be broken down into smaller cycles, where you only develop what’s required to have a branded solution in-market within that timeline.
After honing and perfecting the first milestone, your teams will have flexed all the required muscles to bring an AI solution into the retail environment. Expansion from there will be materially faster. Introduce new next-best-action algorithms, say, to recommend re-fills to existing customers or add more channels like email or app to the recommender.
This milestone-based approach changes the planning and development process. It prepares organisations to adapt and experiment at the speed of AI innovation, while keeping the focus on business outcomes.
Business leaders then need to create the right conditions, by allowing room for experimentation and by recognising speed as part of the brand's OKRs.
The excitement around the adoption of AI solutions has never been as tangible as it is today. Retailers can position themselves to ride this wave by meeting AI innovation with flexible organisational models and partners, and learning new ways to measure success, quickly.