A View From IBM: Challenges Of Scaling AI, Automating And Closing The C-Suite Knowledge Gap

by David O' Toole

As VP & General Manager IBM Automation Europe, Mike Hobday operates on the cusp of two worlds - Industry 3.0 and Industry 4.0, traversing the boundaries between automation and automating at scale and championing the use of “21st-Century tools, rather than 20th century processes”.

After more than a decade at IBM, Mike has spent the past three years focused on process automation, combining robotics and AI, among other technologies, to help move IBM and its client organisations further into the future of work.

Following a tour of UCL Here East, he speaks to Marlin Hawk about the challenge of scaling and the impact of the knowledge gap among senior talent.

Mike, can you tell us what a typical day looks like for you at IBM?

I speak at a conference almost every week, providing IBM’s point of view on automation and the future of work. It’s a really hot topic, but the best part is advising and working with boards and senior leadership at client organisation, across all industries and sectors in Europe.

I’m working with clients who recognise the shift taking place between Industry 3.0 and Industry 4.0. It’s not about finding point solutions, saving this headcount or that cost through automation. It’s about how companies can use automation at scale. Successful transformation across all business lines requires automation in an engineered, governed way that preserves the fabric of the organisation but moves the workforce towards higher value activities that boost the performance of the business, eliminating routine. That’s what my team and I focus on.

A new generation of tools now allows documents and emails to be read, photographs and videos to be understood, conversations to be automated, intent to be determined and enriched with advanced analytics. Together they pave the way to a new workplace in which every role, activity and task has been automated or augmented with AI in some way. 

This future of work, the source of competitive advantage in new AI and robotics enabled operating models, is absolutely at the top of the CEO, COO, CFO agenda.

Lastly, and probably most importantly, I am building a team across Europe in IBM Automation. Given the nature of my work, there are a lot of graduates and apprentices joining me to build solutions that will define the workplace for their generation. 


What challenges are you facing in 2019 that you haven’t faced before?

The problem in 2019 is scaling technology in mature organisations. Companies are asking - how do we take something like robotic process automation and organise in a way that we can leverage it everywhere? Or if we want to use AI or IOT, how do we converge those things in a way that we are solving big business problems, not just isolating them? How do we make them work consistently and correctly at scale, so that the whole organisation moves forward, not just in little pockets?

What we’re finding increasingly is that an engineering mindset is crucial. That is not just the ability to innovate, but the ability to engineer processes so they are rock solid and reusable across an organisation. Then the other big challenge is not new. It is about leadership and discipline in the execution of change programmes, getting stakeholders to work collaboratively across organisational boundaries for the benefit of all.


You co-authored a report on automation in banking and the 'no touch' future. Can you talk to us about cognitive automation and how this is going to reshape the banking landscape over the next year?

The most obvious thing is operational scale, insofar as companies like Lloyds and RBS in the UK and Orange Bank in France are engaging with many thousands of customers every day through artificial intelligence in the form of virtual agents or chat bots. The bots are having increasingly sophisticated conversations, not just addressing frequently asked questions, but also complex product-and service-oriented questions.

The evidence is irrefutable that customers prefer automation over human interaction in the majority of cases where they want a quick answer, and you see the Net Promoter Score (NPS) significantly improving over, for example, webchat manned by human agents.

Organisations like Crédit Mutuel in France, where IBM Watson is consuming and reading 300,000 emails every day, channelling them to the right processes and prioritising response based on urgency. The result – a significant improvement in NPS among staff, as well as productivity across the organisation.

Staying with automation, the CEO of IBM, Ginny Rometty, recently said that IBM can predict with 95% accuracy which workers are about to leave their jobs. Can you talk to us about that?

I don’t get to see that personally, but what I do see is a war for talent. The digital experience of staff is as important as the experience of the customer.  There is a big focus on the ‘employee journey’. How do you make the on-boarding process natural? How do you enable training, HR and IT support, performance management so that it is transparent and tailored to the individual?  For example, virtual agents addressing HR and IT issues interfacing with platforms like ServiceNow are making the workplace a less frustrating space. 

As regards predicting when valued employees may be thinking of moving on –   I am sure there are indicators in behaviours, performance review data etc. which can provide insight and when used in the right way, may enable constructive conversations and provide an opportunity to retain or part with talent on good terms.

What impact will the move towards automation have on an organisation’s senior talent needs?

Firstly, boards and C-suite leadership need to be infused with a better understanding of what technology can do and the outcomes it can deliver. 

Part of the issue is a confusion over taxonomy. If you think about AI, it’s not one thing, it’s many things. There’s a lot of confusion as words are banded around without a lot of agreement on what they mean. If I talk about AI or platforms or neural networks, people’s level of understanding is very different. So somehow, boards have to get to a common agreement over what technology can do, how they talk about it and how they communicate it. That education piece is a big challenge. Because leaders can’t lead unless they understand.

If routine processes have been automated and the focus is on judgement and empathy, then emotional intelligence and the ability to deal with higher volumes and more sophisticated work may mean a shift in recruitment profiling. Getting there is going to need strong leadership, change management skills at all levels.

On the tech front, ‘consulting engineers’ and data scientists will be in demand. Consulting Engineers are able to understand business problems and engineer solutions from a portfolio of automation and AI tools. With data science, there is no doubt competitive advantage will reside with organisations that can mine customer and operational data for commercial benefit.

Do you think diversity has a part to play in meeting that challenge?

Without a doubt. If automation is about designing the new workplace for the 21st Century, then those that build it should reflect the diversity of those who will work in it.