The document discusses the transformative potential of artificial intelligence (AI) and automation, predicting they will generate $15.7 trillion in business value over the next decade. It emphasizes the importance of strategic alignment, investment in infrastructure and skills, and overcoming cultural resistance to effectively implement AI across various industries. Practical steps such as quick-win initiatives and utilizing AI-as-a-service tools are recommended to help organizations leverage AI for improved decision-making and operational efficiency.

1. How To Get Started
AI Journey
With Your

2. © 2020 Bernard Marr, Bernard Marr & Co. All rights reserved
Artificial intelligence (AI) and automation will create $15.7 trillion in value for businesses
over the next decade. Make no mistake, this is the new gold rush, and companies that are
able to understand, adapt and leverage this world-changing technology to meet their
goals have the potential to achieve huge growth.
Of course, for many of us this is easier said than done. AI requires investment, in both
infrastructure and skills, as well as strategic alignment with your wider business
objectives. It also involves working with large amounts of data – the fuel of AI – and this
brings regulatory and compliance issues. Any – or a combination – of these challenges
can be enough to make us feel that AI is not right for us, or not a fit with what we are
doing, or “we will get round to it eventually”. The truth is, it’s been demonstrated that it
can be efficiently and effectively put to use by companies in any industry, and of any size.
The real danger, in fact, is in not recognizing the potential for seismic change that AI
heralds for your industry – and missing out on your slice of the pie.

3. © 2020 Bernard Marr, Bernard Marr & Co. All rights reserved
AI and the associated technology ecosystem, like the Internet of Things (IoT) enables
businesses to grow by improving their decision-making capabilities, streamlining internal
operations, improving their customer offerings and monetizing data streams.
For example, The University of Alabama in Huntsville deploys AI algorithms running on
high-performance computing (HPC) infrastructure, provided by Hewlett Packard
Enterprise (HPE), to help it develop new drugs and treatments for illnesses including
coronavirus. It takes an enormous amount of computing power to build the protein
models needed to understand the effects of vaccines and medicines on virus behavior. By
deploying AI to speed up problem-solving and reduce time-to-value, it is able to carry
out its research using a small team, that is effectively capable of doing the work of
500,000 people.

4. © 2020 Bernard Marr, Bernard Marr & Co. All rights reserved
Similarly, Houston-based CenterPoint energy used to send out armies of human meter-readers
to conduct 80,000 meter readings a day. Today, it receives readings from 221 million meters
every day, automatically, giving it access to far more accurate and up-to-date information to
base its business decisions on. This has led to an 835 per cent increase in the amount of data it
is generating. However, as well as simply having a more accurate picture of the information its
customers are using, it can apply machine learning analytics to this data to do amazing things,
such as predict where power outages are likely to occur, and route energy more efficiently
through its networks, reducing costs as well as the overall carbon emissions created by the
business. This has also led to a 10 per cent increase in customer satisfaction scores, thanks to
faster resolution of supply issues.
When implemented strategically, AI operations drive changes that have knock-on results
throughout an organization, but at their heart you will always find the principles of improving
predictions and decision-making, better understanding of customers, markets and business
processes, creating better products and services, and building new revenue streams.

5. © 2020 Bernard Marr, Bernard Marr & Co. All rights reserved
Although the first steps often seem daunting, just about anyone can use AI today. We already use
recommendation engines when we shop online, natural language algorithms when we talk to Alexa or
Siri, and computer vision tools to interact with augmented reality (AR) apps on our phones. The same
technologies and processes are all applicable to our businesses.
There are a few practical steps that any company can take to start examining where AI might be a fit
for them. The first step is to identify potential use cases. These are applications of data and AI that
help us achieve our business goals. It’s usually a good idea at this point to focus on “quick wins” –
simple, low-investment projects that will provide quick returns but, more importantly, validate the
efforts we are putting into determining our data and AI strategy. This can be hugely valuable in
winning buy-in across your organization and starting to put a “data-first” culture in place. In my
experience, a lack of this buy-in and culture is a primary reason that AI projects fail to get off the
ground. We can encounter resistance from workforces who have become used to doing things “their
way” and are sceptical of “being told how to do our job by a computer.” However, it’s just as likely to
come from management and leadership – where the attitude is often “I’ve got where I am on gut
instinct, and I’m not going to start doing things differently now!” Both of these attitudes can kill AI
projects before they even get off the ground. Creating quick-win and proof-of-concept initiatives that
generate immediate results and quickly show the value of data-first thinking is a great way to tackle
this.

6. © 2020 Bernard Marr, Bernard Marr & Co. All rights reserved
Launching quick-win initiatives is great, because you don’t have to spend a fortune on
infrastructure investments or hiring skilled data scientists. And today, it’s easier than ever due
to the proliferation of cloud-based, AI-as-a-service tools and platforms hitting the market.
Rather than having to stitch together strategy with technology, data, skilled people to execute
it, and a sizeable governance operation to make sure you’re on the right side of the law, many
end-to-end solutions are now available.
A great example are the Accelerate AI “bundles” developed by HPE. These are designed to help
businesses immediately start tackling challenges around working with massive data volumes,
siloed data, security and privacy, and acquiring the skills and talents needed. Since you need
high compute power for AI, package bundles include GPU resources provided by Nvidia as well
as access to the HPE Ezmeral edge-to-cloud digital transformation platform. Crucially HPE also
provides five days of consulting, delivered by the HPE Data Practice Team. They will help with
developing your first use cases for AI as discussed above, from conception to implementation
of your first proof-of-concept or pilot project. They also work to provide education for your in-
house teams, to secure that all-important buy-in. These HPE AI Bundles are available as-a-
service or pay-per-use consumption model, called HPE GreenLake.

7. © 2020 Bernard Marr, Bernard Marr & Co. All rights reserved
With tools like this, even smaller companies can have the resources at their fingertips to make sure
they’re at the forefront of the race towards AI-driven business, and the treasure trove of value that will
undoubtedly come with it. If you’re a retailer, you can segment and target customers with
recommendation engines and personalized marketing campaigns. Manufacturers and producers can
run their operations more efficiently and with less waste, and service providers can offer their
customers smart, data-driven platforms and tools that are more in-line with their needs. In my
opinion, the heroes of the “AI revolution” – those who eventually generate the trillions in value - won’t
necessarily be highly academic data scientists, or working for companies like Google and Facebook.
Big breakthroughs will be made by business-minded, data-savvy individuals with bright ideas and
access to powerful cloud-based solutions. Multiple AI & Big Data Analytics Sessions will be available
at HPE Discover (virtual free event): THE FUTURE IS EDGE TO CLOUD

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