Artificial Intelligence (AI) And Smart Process Automation

The power of what we call artificial intelligence (AI) in business today – generally machine learning – is its ability to make predictions. We can use those predictions – which might be about where we can make sales, or how we can improve customer experience, or our own internal processes – to make better decisions.

Crucially, it means we can also let machines make decisions. This has enabled a wave of smart process automation which is quickly changing many things about the way we do business. Machines are no longer limited to automating "mindless" repetitive tasks- executing scheduled actions such as importing and exporting, moving things to a pre-assigned destination, or applying the logic of a pre-programmed set of instructions. They can be applied to problems that would previously have required the attention of human experts, to jobs like identifying customers that are in-market, or identifying fraudulent financial transactions, or diagnosing illness from medical imagery.

By applying these processes to routine, everyday challenges faced by any business, human work time – perhaps an organization's most valuable asset – can be conserved for work where it's truly required. This is a strategy that's been enthusiastically adopted by companies. Forester analysts estimate the size of the market providing solutions in the smart process automation space will grow to close to $3 billion this year.

However, working with companies of all sizes across many industries to improve the way they use data, one thing I have noticed for sure is that not everyone is getting it right. There are challenges, both technological and cultural, that must be overcome if proof-of-concept and pilot projects are going to lead to real, repeatable improvements to processes and efficiency.

One of these is a need for unity between new, smarter processes and existing legacy tools and infrastructure. Many companies have invested heavily in automating their "front-of-house" – the processes such as sales and support that sit squarely in front of their customers. At the same time, back-office functionality – production, logistics, quality control – remains mired in inefficient manual processes. For the customer, this can create a jarring disconnect between the streamlined efficiency of their online interactions and the mundane reality of the delivery. Imagine ordering food to be delivered from a flashy app interface that does a great job of helping you choose what to eat and place your order, but when it arrives, it's cold and stale. This, too often, is a good analogy for the service provided by businesses in the early stages of transformation to an "as-a-service" model, in my experience!

?Another problem that frequently occurs is that processes are automated with no real thought as to whether the processes are right in the first place. If a process is simply recreated digitally with AI replacing human decision-making – think of a chatbot that routes customer enquires based on the content of emails to customer support – then very often, the result is just automated inefficiency. This frequently happens when businesses decide they want to use a piece of technology and look for a problem that it can solve. Really this is back-to-front thinking – with technology as the first consideration rather than customer experience!

The more sensible approach is to identify a problem, design the process to enable that outcome by orchestrating technology and organizing people to solve it. If you can do this, you're getting close to what Cognizant's global head of intelligent automation, Girish Pai, calls "front-to-back" thinking when we spoke recently.

Cognizant’s suite of intelligent automation tools – called Neuro – is designed to help businesses tackle this issue, as well as another common problem that arises. Often, automation solutions have been constructed with a “pick and mix” approach, with different tools and platforms that have been chosen for their ability to automate one particular task. They may have difficulty talking to each other, and insights discovered in one area of the business can remain siloed, even though they have uses and implications across the board.

The philosophy behind Neuro is that it acts as a "fabric" – sitting across existing automation infrastructure in a way that makes it invisible to the end-user. This is done in a non-invasive way – the tools continue to operate as they always have done. But it aims to provide users who aren't data and automation experts the ability to create, track and evaluate automated processes from a streamlined user interface.

Pai tells me, "We want to offer holistic, end-to-end transformation … our customers want something that is intuitive, easy-to-scale, and speaks to a layman or end-user in terms of what needs to be done … the ability to offer a low-code or no-code interface that lets them embrace technology without having to worry about what technology is doing behind the scenes."

These solutions not only help workforces get to grips with the technological side of smart process automation, but they can also help adapt to and overcome cultural challenges.

People can sometimes be resistant to technology-driven change if they don't understand it, or don't trust it, or perhaps worst of all, if they think that technology is going to take over their role and make them redundant. It's a very real fear that, historically, has often led to a hostile attitude towards technology simmering away beneath the surface of an organization.

User-friendly solutions built around streamlined and efficient user experience are, in my experience, the best solutions to this problem. Employees must see that automation technology can make their lives easier- cutting down their mundane, repetitive workloads through automated decision-making and augmenting their own capabilities, rather than threatening to replace them. When this happens, they become far more accepting and willing to engage or experiment with technology. This shift towards a "democratization" of technology promises to put its transformational abilities into the hands of those who know how to solve business problems but may lack the technical competence to build their own solutions – and that can be a hugely powerful thing.

In the context of the Neuro platform, Pai puts it like this: “While you can be clear on your outcomes, if you’re not clear in terms of how you’re taking people along, you will struggle … what I’m particularly proud of is the ability to keep the technology away from people who are not coders or developers – we want to keep it human-centric, so the user experience is visible, but the tech behind it is not.”

Although we are clearly still very close to the start of the journey that AI and automation will take us on as it transforms businesses and society, we've already experienced a sea change in how we are tackling the challenges that arise along the way. Rather than a patchwork of discreet, developer-led solutions that are applied as and when technologies emerge, my experience suggests organizations that adopt this holistic, people-first perspective are setting themselves up for success. The best process automations are those that improve the experience for business users or customers and free up humans to do the things that machines still can't do nearly so well, involving capabilities such as imagination, compassion, and creativity.??

For more on the topic of artificial intelligence, have a look at my book ‘The Intelligence Revolution: Transforming Your Business With AI’.

Thank you for reading my post.?Here?at LinkedIn?and at?Forbes?I regularly write about management and technology trends. To read my future?posts simply?join my network here?or click 'Follow'. Also feel free to connect with me via?Twitter,??Facebook,?Instagram,?Slideshare?or?YouTube.

About Bernard Marr

Bernard Marr?is a world-renowned futurist, influencer and thought leader in the field of business and technology. He is the author of 18 best-selling books, writes a regular column for Forbes and advises and coaches many of the world’s best-known organisations. He has over 2 million social media followers and was ranked by LinkedIn as one of the top 5 business influencers in the world and the No 1 influencer in the UK.