Leveraging AI in Retail: Opportunities and Challenges

Author, Craig Summers, Managing Director at Manhattan Associates.

The level of Artificial Intelligence (AI) has undeniably grown for retailers of all shapes
and sizes across many sectors. In today’s world, retailers are beginning to develop a
legitimate recognition of what it takes to properly appraise, develop and generate AI and
ML enabled solutions of the future, moving past the marketing outbreak that AI once
was.

Moreover, despite the developments that have been contrived, some retailers have not
yet acknowledged the true possibilities of AI and what this entails. It is these retailers
that need to question themselves: what do we want to accomplish with AI? What can AI
really deliver – and what will this mean for our customers? Craig Summers, UK
Managing Director, Manhattan Associates encourages retailers to leverage AI to its
greatest potential – from the beginning stages at the warehouse to the end result at
stores – in order to deliver a joined-up customer experience that is right every time.

The Power of AI
The opportunities to leverage AI and ML to improve retail operations are exponential for
either online, in store or in the warehouse – especially as research estimates that
retailers will spend $15.3billion on AI by 2025, $8billion more than initially projected by
the end of next year. However, before AI can be truly powerful in the sector, the hurdles
of data quality and quantity must be addressed initially.
Even with the magnitude of data currently captured by many retailers, they repeatedly
struggle with capturing and retaining enough of the ‘better stuff’ – historical data that is
factual, complete and textual – to take full advantage of the benefits AI can put forward.
This data is fundamental to make AI and ML models the best they can be. In the rush to
grasp innovation, it is easy to overlook the challenges presented and move focus away
from the essential objectives, which should be: where is the ROI, and what is the
implication for the customer experience?

In Practice
Take, for example, a great AI solution in store that gathers information about a
customer – such as hair colour/type and skin tone, size and style – to recommend new
products, from hair styling to make-up, fashion to accessories. This would be extremely
enticing for customers, especially due to the pandemic with minimal contact and social
distancing. However, unless every suggestion made by the solution is easily accessible
for customers to buy in store at that very moment, or if not, easily sourced and delivered

to the customer’s destination of choice, using AI in this way helps contribute to a
satisfying customer experience that is enduring and profitable on the bottom line.

Future Goals
With the future of various high street stores remaining questionable, getting the
customer experience right at every opportunity – which means encouraging repeated
visits – is critical. In today’s highly competitive retail landscape, ridden by challenges
from Covid-19, consumers continue to face seismic hurdles with offline and digital
worlds. Therefore, it’s crucial to understand the key benefits that new technology will
bring, including the customer experience implications.
Today, customers will seek different retailers within the overloaded omni-channel
marketplace if products can be delivered efficiently as well as being at a lower price
elsewhere. Strong customer experience and satisfaction are not achieved through
technology gimmicks, but through ensuring technology can help customers quickly get
their hands on the products they are searching for before it’s too late.
In practice, this means ensuring maximum stock availability – where it is needed, at the
correct time, and at the right location. It means achieving a slick warehouse and
distribution centre operation that can fulfil both to the store and to the consumer's front
door whilst adhering to social distancing requirements. AI solutions will add positive
value when this structure is in place.

Change is good
Retailers that have utilised AI in the warehouse are already driving tangible
developments in efficiency and accuracy. By combining deep, high-quality order history
data with AI and ML to greater grasp the aspects of purchasing trends, including direct
to consumer ecommerce orders, retailers can reconsider the pick, pack and ship
operations. Schedules are being re-organised and resources rearranged, while orders
can be seamlessly prioritised and new delivery choices enabled.
In addition, AI enables retailers to better manage the changing sales peaks: for example
the back to school rush or a sudden April heatwave. The huge rise in ecommerce
orders experienced when stores closed their doors last year, indicates how retailers
need to be well prepared if a new peak suddenly emerges.
With the help of AI, retailers can take advantage of accurate and granular predictions
that can be utilised to smooth out the entire logistics process and efficiently respond to
challenges in real-time. With innovation at the core of AI, retailers of all types and sizes
can use the myriad of AI and ML opportunities to level the playing field with giant

retailers, to help neutralise and compete – but also to differentiate. Retailers have also
shown in the past how they can embrace innovation, adapt to a challenge and adopt the
technology available – and there has never been a better time for them to achieve this.
AI is taking retail by storm, however, putting the gimmicks aside: the real and attainable
value of AI currently is to be gained by applying proven algorithms to drive fundamental
supply chain developments.