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AI and Executive Education: Why it is important to understand the value of data
Executive Education / 16 December, 2019
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Certified Specialist in AI for Business
Sarah Rojewski ist Digital Service Manager bei der Telefonica GmbH & Co. OHG und Projektleiter für die Implementierung der globalen künstlichen Intelligenz von Telefonica "Aura". Sarah ist die Schnittstelle zwischen den Geschäftsanforderungen von Digital Transformation und Technologieanbietern wie Microsoft und Amazon Web Services.

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Society is gradually but inexorably becoming aware that because of huge advances in AI in general and Deep Learning in particular, we are about to enter a fourth industrial revolution. Even so, many people are still unwilling to confront this fact, refusing to acknowledge the inevitability of change. Although this trend, along with the associated opportunities, is clear, the principles themselves are not always well understood.

As Digital Services Manager and Aura Project Manager at Telefónica Germany, I face the challenge of making people aware of the latest AI developments on a daily basis, which means keeping up with the fast-moving and disruptive digital transformation involved. Aura is Telefónica’s global artificial intelligence system which, combined with lower-level AI, is set to catalyse lasting change in today’s customer services and sales business model. For our customers, Aura represents the new, key element in interactions with the company and, as such, will be omnipresent. By implementing Aura, we intend to build a new kind of customer relationship based on trust in AI. Contacting our company should be easy, not restricted to working hours. Aura is capable of understanding natural language, answers questions in real time, is available 24/7 and can help with any kind of inquiry. And if the AI itself reaches the limits of what it can do, it refers the issue to the appropriate human specialist. As far as the ethno-ethical aspect is concerned, we prefer to be transparent: We always let customers know that they are interacting with an artificial intelligence that has no specific shape or gender and is not a “real” human employee.

First contact with AI

As a Humanities graduate on the cusp of taking responsibility for “cognitive intelligence” applied to Customer Services, I found myself facing not just a major project, but also a (very) steep learning curve. Lacking a technical background, I was plunged into the deep end, expected to “learn by doing”. I read up on AI and machine learning and communicated directly with the developers and data analysts in Telefónica’s IT department and data warehouse. My colleagues’ input was heavily characterised by their development perspective, so the information they provided was rarely delivered by someone who could give me an overview from a business perspective. This meant that there were great gaps in my basic knowledge, not least because I didn’t have the right contacts to talk to. Even so, I enjoyed considerable success in tackling the project within the company, but to dispel any remaining uncertainties, decided to enrol on an executive education course.

My search for the right course threw up several very promising results, but most executive education courses covering digitalisation are very broad in scope. However, Frankfurt School’s Specialist in AI for Business certification course focuses explicitly on AI, and that’s why I opted for the three-day workshop.

I was hoping that the course would give me more confidence in general – and above all, sufficient confidence to make serious progress in implementing Aura within the company. You need to be able to convince people to invest resources in AI, because the costs are not negligible. The prospect of a workshop in which I would be able to directly address and discuss specific use cases related to our business activities was something I felt would be very useful.

The training course itself

After I provided a brief description of the executive education course, Telefónica Germany authorised and funded my participation without demur – they too could see the potential benefits. Enrolling went very smoothly, and I attended the three-day workshop at the end of November. First of all, we were given an overview of the latest developments and trends, followed by a more detailed introduction to the underlying principles. The workshop gave participants plenty of space to present their own real-world examples and then discuss them in detail. The atmosphere was great, because the lecturer had carefully structured the content and used a wide variety of media and teaching methods to convey it. In the process, we discovered that successful companies such as Google or Facebook no longer make traditional presentations, but prefer to use a more agile approach and media mix. We experienced the added value of this approach at first hand – instead of just listening to monologues, we were actively involved in deciding how best to fill our three days of intensive study, while simultaneously benefiting from Mr Andonian’s extensive knowledge of the field. There was always time for lively debates and questions. Workshop participants came from a wide range of industries, which made our discussions of real-world examples even more interesting. And afterwards, all workshop content was made available in digital form, so we could access it wherever and whenever we wanted.

How things worked out once I became a “Specialist in AI for Business”

Just two weeks after the workshop, I am already making excellent progress. I arranged an appointment with our data warehouse team immediately after the course because I am now in a position to ask directly relevant questions and understand the answers. Consequently I was able to gauge the precise status of current operations, discover which models we were already using, and find out what data was being used where. This has enabled me to devise new use cases for Aura, with the focus on reusability and cost efficiency. For the future, we have defined an Aura roadmap with 10 use cases. These go far beyond conventional API calls, featuring data models for even more personalised use cases. In September, I will take part in the course’s second workshop and am already looking forward to finding out more about applied AI. In my job, I will never be required to do any programming myself, but what I have learned and am learning will help me to formulate requirements and identify problems and obstacles. My job involves acting as the interface through which all AI-related workstreams converge, which is why I can only benefit from understanding the relevant programming principles.

I would recommend Frankfurt School’s executive education courses to anyone who doesn’t want to be left behind by state-of-the-art technology. But first and foremost, I would recommend them to all businesspeople who want to speak the same language as their colleagues and stakeholders.

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