An experienced technology leader, Dr Nicola Hodson joined IBM from Microsoft in January 2023 and brings deep technology industry expertise, as well as extensive experience in business and digital transformation, sales and IT in leading global companies.
Technology Magazine recently sat down with Dr Hodson at IBM Think in London to discuss IBM’s approach to AI, the importance of ethics and what the company’s future looks like.
Please introduce yourself and tell us about your role
I joined IBM in January and my role is Chief Executive of IBM UK and Ireland. My role has multiple facets to it. First and foremost, that is to make sure that we are best supporting and serving our clients. Secondly, it’s that we build out a partner ecosystem, which is a major facet of what IBM does across the UK and Ireland. I also lead our people across the UK and Ireland, making sure everybody's energised, motivated, up to speed with our latest technology, and able to bring that to support our clients.
In addition to that I do a lot of external work with clients, with partners, with the UK government, and making sure that we create the climate in which we can do business. Increasingly, we're involved in policy matters, especially as it comes to AI regulation, AI safety, AI ethics and how you build a governance framework to make sure your AI models are doing the right things.
Of course, I am accountable for business performance. It goes without saying that the UK and Ireland is a big part of the organisation and it's important that we're able to bring the best of our technology and our consulting expertise to bear here.
How important is AI to you at IBM?
IBM has a really clear strategy about how we help and support our clients to make the best of advanced technology, and those technologies that we're focused on are hybrid cloud and AI.
When it comes to hybrid cloud, 77% of all clients have a hybrid cloud environment, be it public cloud, on-premises, or any other private clouds you might think of. So being able to act across all of those environments is super important.
The other big component is AI. It's a big theme for IBM and something we've spent many years of R&D and effort on. Most people will be familiar with our brand, Watson, and this year we launched watsonx. We believe that every company and organisation will become an AI organisation.
At IBM we are differentiated primarily in the fact that we're all about AI for business. We don't play in the consumer space, it's all about AI for business. Businesses have very specific needs for AI. It's not like I'm off to do a restaurant search for somewhere to eat tonight: the stakes there are not very high. But if I'm a business, for instance a bank or a healthcare provider, and I'm helping you to make a decision or giving you information, I’d better hope it's going to be right. I’d better hope it's going to be explainable and that it's not treating you any differently because of who you might be.
Businesses absolutely need consistent AI, and that's our specialist space, and that's where we believe watsonx really comes to the fore.
Tell us about the importance of ethics when it comes to building AI models
We spend a lot of time talking about AI regulation and AI ethics to make sure that we can exist within a framework that supports the responsible development of AI. You have to think about the components of responsible AI at the get-go, not once the genie's left the box.
If you think about responsible AI, it's really important that we work in every country where we operate – with the government, with regulators, with other partners and with industry and academia – to make sure that we've got a regulatory environment that fosters the development of responsible AI.
For us, that means you regulate the use case and not the algorithm. Many countries are going down the former route. We think the UK is on the right track going down the route of regulating the use case which might be where you, as a human, interact with the AI.
We think AI regulation has to be done by specialist regulators. The FCA or the PRA need to regulate banking and the financial services sector because they know about the sector, they know the risks. It doesn't make sense to have a new regulatory body when you've got people steeped in that industry.
When it comes to ethics we have three pillars: we look at the principles, the practice, and the policies. Think of the principles as how you govern AI and make sure it's fair, explainable and transparent. And every organisation needs to think about that because let's face it, your reputation is on the line if you're using this technology in practice.
The second is about practices. That's about making sure as you go all the way through the development life cycle, from design through development and deployment of AI. It’s crucial that you're thinking about ethics all the way through that cycle and making sure, again, that the process is fair, explainable and transparent.
And then the third is about policies. That's a bit more widespread than regulation in a sense that you want to make sure that the policies in place support AI development that isn't advantageous or disadvantageous to any section of society.
That gives us the best shot at making this a success not just for a few, but for many people and really taking advantage of the hundreds of billions of pounds that AI can add to the UK economy.
Tell us about watsonx and what it offers to your enterprise customers
Watsonx has three basic components: watsonx.ai, watsonx.data and watsonx.governance, and it works across any cloud. 77% of organisations have a hybrid cloud strategy. So it's super important that you're not saying, ‘Hey, this only works if you extract all of that data from all of those clouds and put it in one place’. We don't need that to happen. Watsonx is built on Red Hat OpenShift and it allows your data to sit wherever your data sits and for you to then be able to access that to reason your AI across that data.
Governance is about lots of the things we've been talking about so far, which is how you validate, train, tune, and deploy your AI models, and how you do that in a way that you know where the data came from, whether it's trusted, whether it's verified and how your AI is reasoning over that data and taking its decisions.
The second piece is around watsonx.data. AI is only as good as the data it's reasoning over. So for many years in the technology industry organisations have been grappling with how to get their data in good shape. Interestingly, with watsonx, it means you get the benefits of a data warehouse without having to do those multi-year complex programmes to build one.
Then the third part which we talked about is watsonx.ai, which gives a bunch of different capabilities including Watson Orchestrate, as an example, which allows you to automate processes.
A good example in our own world is we transformed IBM's HR function on a global basis. The work of 700 people is now done by 70 with the support of AI. It has really transformed the employee experience. The other HR professionals didn't go anywhere other than to go into higher value work or to be redeployed into different parts of the business, but they're now doing a lot more work to support people on career development and talent management.
How important are partnerships at IBM?
IBM launched a programme in January this year called Partner Plus, and it's a real step forward in our approach to the ecosystem. We are very reliant on a vibrant ecosystem.
If you own three DIY shops and you want to implement AI, you need a partner around the corner whom you can contact and can support you. And so, we absolutely need a vibrant ecosystem of partners, from the large to the very small.
We partner extensively with people you might think are competition: AWS, Microsoft Azure, Adobe, SAP, all the way down to small mom-and-pop shop partners. It creates a model where we incentivise them to get certified in our programmes and that gives more of a pull factor. We also now have a number of our products and services available online and we are able to pass leads directly to those partners now.
We also recently announced for the UK market the availability of the majority of IBM software and products in the AWS marketplace, as an example. So it just gives customers more flexibility. We know that clients across the patch will want to work with multiple vendors. It's perfectly natural and our aim is to support them as best as possible in that.
What does the future look like when it comes to AI at IBM?
One of the things we will continue to do is make sure our business is first and best and making sure we're applying that technology and making ourselves more productive and giving our employees a better and better experience.
We are very active in building an ecosystem. If you think about the UK market specifically, the UK is third only to the US and China in terms of AI capability and AI startups.
Where we are not always so good is the adoption of that technology. And so, success for me in this market looks like making sure that we have sufficient capability and capacity in our channel to drive that adoption to make sure everyone's skilled and able to take the technology on and move through to advancement.
As you think about the evolution of the workforce and how you help society make the best use of AI, I think we all in the tech industry – including IBM – have a very big part to play in making sure we skill up the population. All of our jobs will adapt. We need to be able to interact with AI systems and keep building our own skills and those of the people around us so that we can take best advantage of that.
I think success looks like getting hold of the £635bn pounds available to the UK economy and helping it to stay at the forefront of AI and making sure our businesses and people thrive. That is a large number, and if you think about that divided across the households in the UK, the impact on health and wellbeing could be phenomenal. If we can go after that, the UK becomes successful, UK businesses become successful, all of our clients are successful and we are there to support them to do that.
