Workforce Planning and Management

Q&A: AI & The "Industrial Revolution" in IT


Artificial Intelligence Q&A with Ergun Ekici – VP Emerging Technologies, IPsoft.

How do you feel AI is changing business processes at present?  And can you define what you mean by AI in this context as this can cover a spectrum of different things?

I define AI as a cognitive machine that can understand what it is being told via natural language, learn continuously and subsequently solve problems by applying its knowledge. In a business context, this means being able to interact with humans naturally, explore what issue needs to be resolved and figure out what actions need to be taken.

By this definition, AI opens up a massive opportunity to enhance and automate the huge number of administrative and knowledge-based roles that have arisen over the last 40 years to support core business processes. Expert systems using autonomic technology are already automating management and administration tasks within the IT department, freeing up skilled IT engineers to focus on work that creates value for the business. These virtual engineers learn from how a human engineer tackles a problem that they haven’t encountered before, so they can fix the issue the next time it happens.

With cognitive AI, virtual agents, operating outside of the IT department, will learn from humans – actually “observing” interactions and absorbing the lessons drawn from that experience – in a similar way to a new employee shadowing an experienced colleague to build on their formal training.

As the technology matures and we begin to apply it to knowledge-based roles, AI will offer businesses the opportunity to both improve the quality of core business processes by removing human variance, and rapidly scale processes to manage operational peaks and troughs.

A wireless carrier could not only automate the handling of incoming customer service queries, but also take advantage of the ability to quickly scale to redesign the business process and offer proactive customer service. Utilising AI, it could immediately make outbound calls if a service issue occurs and offer assistance no matter what language the customer speaks, or what time of day or night it is.

AI can also help humans manage the immense increase in data available in order to make better business decisions. Think of a virtual doctor’s assistant, who could make diagnosis and treatment recommendations based on what it has learnt from medical text books, observing how doctors apply their knowledge, and reading data from a wide range of sources on new treatments. The doctor will still make the final decision on what actions should be taken, but the patient would be assured that no relevant data point has been overlooked.

We are not far away from realising this level of AI.


In your opinion, how will this develop in the medium and longer term?

We have made great strides in the ability of AI to understand what is being said and apply that understanding to interact in voice and text. But words are only a starting point. The next step is incorporating emotional and empathetic modelling in AIs. That is, teaching robots to understand visual and audio cues – not just the sentiment conveyed by words but by inflection, tone, body language, and facial expression – and then training them to respond accordingly. This is still a fledgling field of research within the AI landscape, but will be key to taking the deployment of AI to the next level.

As the strands of AI technology mature, so the scope of deployment will expand from more controlled environments within businesses in which staff will interact with a mix of ‘virtual’ and human colleagues, through to consumer-facing processes that demand a broader variety of human interaction.

100 years ago, factories and assembly line facilities were designed to support 500 human workers. Today, many of those manufacturing facilities are dominated by robots, not people.

Organisational processes will evolve in a similar way to accommodate AI. Many business processes today are built to accommodate the strengths and limitations of humans, but these will be re-envisioned to leverage the capabilities of AI alongside employees. With this change, the potential impact of AI will increase still further.


Can you describe the “industrial revolution” within IT and what this means in practice? This is a term which gets bandied about a lot, why is it really an ‘industrial revolution’ this time?

There are clear parallels.

Industry started with highly skilled, highly specialised individual labourers such as blacksmiths and silversmiths. Over time, labour was commoditised into an assembly line, where each individual carried out less skilled and more repetitive tasks. In the third phase, machines were deployed to take over repetitive tasks and allow human to focus on creativity, process management and improvement.  Instead of tightening the same bolt on a car door every day, human engineers could concentrate on designing a better car door.

Just as there were blacksmiths and silversmiths, highly skilled mainframe engineers once dominated the IT industry. About 40 years ago, we began to see the emergence of the commoditised labour stack. As we introduced standards and processes into IT, we enabled labour arbitrage, allowing less skilled, less specialised offshore labour to take over IT operations. In the last half decade, the IT revolution has made the leap to the third phase, where robotic systems assume the role of the offshore labour.  Virtual engineers are being trained to take over L1/L2 tasks across event, incident, request, change and release management. Human engineers can then focus on problem management, service design and service technology.


What are the challenges of deploying these solutions in the workplace?

Although the potential impact of applying AI to business processes has similarities with the use of robotics in the manufacturing industry, the key difference is human interaction.  You’re unlikely to know what percentage of your car was built by a robot, as manufacturing happens away from customers.

AI in business is fundamentally different. The technology needs to reach a point at which customers are comfortable speaking with a virtual agent and will trust it in a natural dialogue as much as they would a human. In effect, AI needs to pass the Turing Test for business. 

When it does, many CEOs will be motivated to deploy it to achieve a competitive advantage. They will also have to decide how best to re-purpose roles to drive most value for the business and carefully manage the change in working practices.

Each early deployment will teach new lessons in the subtleties of redefining the human-machine relationship. The quicker AI technology providers and businesses embed those learnings into the systems and processes involved, the quicker the inevitable resistance to change will be overcome.


How do you see these developments fundamentally changing the workplace of the future? Can you include a timescale?

In the next five years, a majority of enterprises will adopt – if they haven’t already – expert systems, robotics and virtual agents or assistants. Within five to ten years, it is unlikely anyone will not interact with these technologies on a daily basis at work.  Much as we witnessed the reshaping of processes to exploit the fast evolution of communication technology including email, cell phones and text, we will witness a similar evolution impacting how employees interact due to AI.  

Initially, AI adoption will focus on making the business processes we use today far more efficient and equip us to manage higher volumes of data, as well as customer interactions. The next five years will see the development of radically different businesses processes as the potential of AI is better explored.   

Humans will have the opportunity to concentrate their brainpower and ability for innovation on devising those new processes and utilising the technology to shape new roles. Change is always a challenge, but for those who seek to harness AI technology to reach new horizons, the opportunity will never be greater.  As knowledge workers hand over the more mundane and repetitive parts of their jobs, they open the door to playing a more rewarding and intellectually stimulating role than is offered to many today.

The next decade will be telling. The technology is here. The speed of change in the workplace will be dictated by appetite for change rather than any limitations in the technology itself.


This May IDG Connect produced a special report: “Is 2014 the Year of Artificial Intelligence?” 


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