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.

1. And Smart Process Automation
Artificial Intelligence (AI)

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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.

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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.

4. © 2020 Bernard Marr, Bernard Marr & Co. All rights reserved
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!

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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.

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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.

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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.

8. © 2020 Bernard Marr, Bernard Marr & Co. All rights reserved
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.

9. Bernard Marr is an internationally best-selling author, popular keynote speaker, futurist, and a
strategic business & technology advisor to governments and companies. He helps
organisations improve their business performance, use data more intelligently, and
understand the implications of new technologies such as artificial intelligence, big data,
blockchains, and the Internet of Things.
LinkedIn has ranked Bernard as one of the world’s top 5 business influencers. He is a frequent
contributor to the World Economic Forum and writes a regular column for Forbes. Every day
Bernard actively engages his 1.5 million social media followers and shares content that
reaches millions of readers.
Visit The
Website
© 2020 Bernard Marr , Bernard Marr & Co. All rights reserved
© 2017 Bernard Marr , Bernard Marr & Co. All rights reserved
© 2020 Bernard Marr, Bernard Marr & Co. All rights reserved
Bernard Marr is an internationally best-selling author, popular keynote speaker, futurist, and a
strategic business & technology advisor to governments and companies. He helps
organisations improve their business performance, use data more intelligently, and
understand the implications of new technologies such as artificial intelligence, big data,
blockchains, and the Internet of Things.
LinkedIn has ranked Bernard as one of the world’s top 5 business influencers. He is a frequent
contributor to the World Economic Forum and writes a regular column for Forbes. Every day
Bernard actively engages his 1.5 million social media followers and shares content that
reaches millions of readers.
Visit The
Website

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