Three changes retailers need to make to embrace the power of AI
There is no doubt that AI is on the cusp of unlocking the next wave of productivity across the economy.
A recent report by McKinsey & Company stated that generative AI could add $2.6 to $4.4 trillion of value to the global economy annually with 75% of the benefit derived in customer operations, sales and marketing, software engineering and R&D (The Economic potential of generative AI - The next productivity frontier - June 2023).
Generative AI’s ability to understand natural language will enable the automation of a significant number of corporate tasks and processes. At the same time, predictive analytics will make organisations more efficient by enhancing accuracy of commercial decision making.
These developments will change the way we work. AI will have more impact on knowledge work associated with occupations that have higher educational requirements (and wages) and the pace of workforce transformation is likely to accelerate, given increases in the potential for technical automation.
There are three key areas that stand out that must be tackled before retailers will be able to take advantage of the potential productivity gains.
1. Get the data right
Most retailers are early on in their data journeys. Data tends not to be managed well living in different parts of the organisation, not connected, not clean and not reliable. The best competitive advantage a retailer has is what they know about its customers that others don’t. For example, data combined with AI enables:
i. deeper customer understanding, segmentation and personalisation
ii. accurate forecasting demand and therefore stock optimisation and staff scheduling based on historic trading patterns
iii. predicting demand sensitivity to price changes enabling pricing optimisation
iv. store or warehouse pick and delivery route optimisation
v. deployment of chat bots to automatically answer customer queries
These above examples, amongst others, enable the building of a meaningful connection with customers and meeting or exceeding their expectations. It will also reduce costs through automation of tasks and processes and removing human bias.
Data is the secret sauce to long term success.
Therefore, organisations need to invest in building robust platforms and analytical tools. Then build and develop their data teams empowering them to manage, curate, combine and clean the data whilst keeping on top off the data ethics and governance issues.
The data has to become AI ready. Without this, rubbish in will lead to rubbish out, but only faster and precisely wrong!
2. Breakdown silos and build skills
Many of us are working in or have worked in organisations that work in silos often with little visibility of data or initiatives across teams and departments.
For AI to succeed silos need to be broken down so that data can be meaningfully connected across the organisation and end to end customer, process and cost outcomes properly understood. At the same time colleague AI skills will need to be developed across the whole organisation (top to bottom) so that all colleagues are working towards the same outcome with the same level of understanding.
In addition to management teams relentlessly living and leading in this direction, retailers should consider developing:
i. Cross-functional AI teams: creation of teams consisting of data scientists, IT experts, and business stakeholders. For example, a team may include data scientists responsible for developing AI algorithms, IT experts who ensure the seamless integration of AI systems, and business stakeholders who provide relevant expertise and insights. Together, they collaborate to identify opportunities, solve challenges, and implement AI solutions across various departments.
ii. Customer engagement teams: linked to the above, a team that brings together marketing, sales, and AI specialists. This team collaborates to leverage AI technologies in enhancing customer experiences. They could deploy AI-powered chatbots for customer support, personalised product recommendations based on behaviour, or AI-driven social media analytics to better understand preferences and sentiments.
iii. Upskilling and training programs – to be run continuously and effectively. Colleagues should be encouraged to acquire skills outside their traditional roles. For example, colleagues on the sales floor could receive training in data analysis to leverage AIgenerated insights for personalised customer interactions. Similarly, data analysts could learn about retail operations to better understand how AI can optimise processes and drive efficiencies.
Building a continuous learning mindset among colleagues and emphasising the importance of staying updated with the latest AI advancements will go a long way to developing the right conditions for AI to succeed.
This image has been generated from Stability.ai Dream Studio using the prompt ‘An image depicting the transformative power of AI in an organisational setting. The AI technology is seamlessly integrated into the workplace, driving innovation, efficiency, and collaboration’.
3. Embrace organisational change and develop an experimental mindset
AI implementation is an ongoing journey that will require organisational flexibility. There are many developments happening on a weekly basis and much to keep on top of in addition to the day job.
The best way to understand how AI will fit is to experiment and play with the technology. Try to understand it. See what things it’s good and bad at. The more organisations experiment, the better they will get a grasp on what AI is actually capable of. There will be failures along the way, but these must be celebrated, learned from before moving on to the next experiment.
AI makes data accessible to everyone, fostering collaboration where it wasn’t possible and enabling decisions to be made much faster and more democratically. Retailers must then be willing to adapt their people structures and processes to accommodate AI-driven changes. This will involve restructuring teams, creating new roles or redefining job responsibilities. Marketing, customer services and IT are likely to be the most impacted in the near term.
The future of retail lies in the seamless integration of AI into organisational structures. It is the human mind that enables the beating heart behind AI. By embracing these changes, retailers can unlock new levels of efficiency and customer satisfaction.
Are you ready to shape the future of retail through AI?
About Rajesh Gupta
Rajesh is a strategic executive leader with a proven track record of customer focussed growth and digital innovation. He has over 20 years’ experience in retail holding a variety of senior roles in customer and channel development at Central Co-op, Pets at Home, Sainsbury’s and Argos.
Rajesh is also a Non-Executive Director for Habinteg – a social housing provider building and promoting accessible homes and communities for disabled people.
A big thank you to Rajesh for this insightful article.
We regularly collaborate with clients and candidates to produce original and informative content for our Content Hub, LinkedIn company page, and quarterly newsletter.
If you would like to write a guest post about an area you specialise in - perhaps highlighting your thoughts on the future of marketing, the current challenges and opportunities, or a topic you feel has been overlooked. Or, if you would like to take part in our Q&A video series where Suzie interviews senior marketing professionals, please get in touch: contact@swexecsearch.co.uk
Suzie Walker Executive Search is a firm of specialist headhunters with an expert team recruiting interim and permanent senior leaders for consumer-facing (B2C) and B2B2C marketing and digital roles in FTSE 350 and private equity-backed companies. Find out how we can support you by connecting with a Consultant below.