Artificial intelligence (AI) has the power to change
almost everything about the way the business is done today and
could contribute up to $15.7 trillion to the global economy by
2030, according to PwC's '2019 AI Predictions. Six AI priorities you can't
afford to ignore'.
Beyond the general awareness of what AI could offer is a grey
space of uncertainty about how to successfully deploy the new
systems throughout the organisation so that it does not cease at
the Proof of Concept (POC) stage.
ESCP Europe has developed a strong expertise in the domain of
artificial intelligence through its cutting edge research and
development of two programmes: the
Master in Digital Transformation Management &
Leadership (MIDITAL) and
Executive Master in Manufacturing Automation and Digital
The School has also supported a series of exclusive forums
on this topic organised by the
French Chamber of Commerce in Great
On 26th March 2019 took place the first session of this year's
Digital Transformation and Innovation Forum organised by the CCFGB
and sponsored by ESCP Europe Business School. The CCFG members and
organisations from the construction, retail, trading, legal,
finance, consulting, tourism and banking industries met to discuss
the latest on the development and applications of AI.
The event was chaired by Christophe Chazot (Group Head of
Innovation, HSBC) and Fabrice Bernhard (Founder, Theodo).
Dr Terence Tse, the Associate Professor at ESCP
Europe Business School and the Co-founder of Nexus
FrontierTech presented on the theme
of demystifying AI in the current business
Dr Clément Walter, the Machine Learning Researcher
Sicara, shared a technical case study and showcased
examples from across the industry.
Does artificial intelligence actually exist?
Dr Tse explained that the AI does not have intelligence - a
machine is merely guessing what a person wants to see.
Indeed, intelligence usually refers to logic,
understanding, self-awareness, emotional knowledge, planning,
creativity, problem-solving and learning. Machines can do none of
these. Machines learn by improving their ability to guess
accurately over time and do not learn as we human do. What AI
can do remains, for the time being, very limited.
It is important to bear in mind that, when putting AI into
business, it can only achieve a narrow and well-defined objective.
The technology is best deployed in labour-intensive routine process
What cannot be solved by AI?
As AI can only excel in completing specified tasks, we can
dispel the common misconceptions that we can create AI strategy, or
that AI is going to replace human beings in the job market. We
are likely to see only a partial elimination of our jobs,
unless jobs consist of only one task.
If AI was to be put in use in current business
activities, there should be five rules to follow:
1. Be narrow-minded
It is necessary to clearly define what exactly the outcome to be
achieved by the machine. AI can only do one task well and no more;
therefore, it is important to be clear what the task is.
2. Weigh the risk
If a machine does the work, a human has to be prepared to give
away certain authority and power. It is also important for us to be
happy to assume the potential risk that comes with the use of AI
3. Get the "last mile" right
This is about a back check - the necessity of checking what the
machine produced. It is impossible to delegate 100% of the task to
AI as it carries too great a consequence if mistakes
happen (for example in financial and legal contracts, airport
boarding passes, etc.).
4. Consider less data may mean more
Collecting the right data is much more important than having a lot
5. Do the necessary homework
Technology alone cannot solve problems. It must be accompanied by
the right workflows and processes. Hence, being able to map, amend
and implement the right workflows and processes is absolutely
critical to the success of putting AI into business use.
Dr Tse discussed the countries that lead the way in AI
tech. In terms of advancement in this area, Europe has remained
behind China and the USA. One reason could be that risk aversion
within Europeans is still high, and privacy policies (such as the
newly introduced GDPR) are safeguarding but also preventing
widespread availability of data. Another problem is that Europe has
not really fostered any tech titans, unlike the US and China.
AI and the food recognition algorithm
Dr Walter's work focuses on research and implementation of
machine learning and deep learning solutions at production level.
He spoke about the use of AI for food image recognition to make a
real impact in every day life, and presented a Sicara's case study
on the creation of a food recognition algorithm to facilitate
the workflow in restaurants and canteens.
His work is currently working on the development of an automated
canteen cash desk system based on computer vision algorithms. A
first pilot has been released, which can currently bill 70% of the
served meal trays.
With the first attempts to solve the problem came the Foodvisor
in 2015, a B to C application that allowed the taking of a
photo of food to tell a buyer if the product was healthy or not and
providing a calorie count. With few new players in the market, such
as Elior, Sodexo and Eurest, the AI facilities are yet to
develop to diversify the proposition, reach more sophisticated food
recognition, and provide a faster service within the industry.
Dr Walter's advice for a better outcome at this stage is to be
able to compromise on the performance of the system. The approach
to the system should be pragmatic, starting with small
amendments and, as the data grows, slowly increasing the area of
activity for AI. This could be through setting up two check-out
queues in restaurants and canteens for those foods already easily
recognisable and those not defined yet to avoid major mistakes.
Both speakers agreed that AI is one of the best tools for
increasing productivity and cutting costs for companies as long as
the process focuses on systematic, basic tasks that could be
tackled by algorithm. Only tasks that can be easily defined and
articulated, with clear input and output, should be considered for
any companies taking the first step towards using AI. Customisation
and integration of AI into the existing legacy IT systems remain
the most challenging part of a project.
Watch Dr Terence Tse's
top tips from this session.
Empowering young talent
If you would like to
a future digital leader ready to tackle any business
challenges related to digital transformation & frontier
technologies, we would like to invite you
to attend an online info session about the Master in Digital
Transformation Management & Leadership that we are hosting
on Wednesday, 1st May at 16:00 BST (17:00 CET).
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is specifically designed to help participants prepare for key roles
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increasingly important yet complex business challenges related to
digital transformation and frontier technologies.
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