How To Get Started With Your AI Journey

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.

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. 

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.

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.

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.

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

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

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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.