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Please tell us about your new role and what are your immediate priorities?

As the GM of Technology, I am responsible for IBM Software, Hardware, Technology Lifecycle Services (TLS), Expert Lab Services, Client Engineering, Client Success, Digital and our Ecosystem. My role as the technology ambassador is to ensure IBM technology delivers value to our clients, remain a technology leader in our market and deliver on our commitments to the business. That is clearly not something I can do alone. I feel my biggest responsibility is to ensure the people in our organization work together as one IBM team. Every individual in the technology organization has a key role to play in ensuring IBM is successful and that our clients want to work with us. 

I am very focused on transparency and trust. So I’d say my immediate priority is to ensure everyone understands how important they are to our mission. I want to make sure we communicate and operate as a team because there is nothing more powerful than when IBMers work together.

Every decade or so - there have been unique inflection points in technology – and we are on one with AI. So, how transformative will GenAI be? Or how do you see the significance of this phenomenon?

AI in business is not new, but it has significantly gained momentum with the advent of generative AI. We went from a place where AI was being used by some enterprises for some value to, all of a sudden, a mass amount of people around the world rapidly interacting with it, seeing how easy it is to use, and getting a tremendous amount of value from it in a really accelerated period of time. People now are more aware of AI, they have tried it, liked it, and are starting to understand its impact. But the question really is whether they use it on a regular basis. This is where AI can become really impactful.

As one of the most transformative technologies of our time, AI has the potential to boost productivity and unlock trillions in economic value over the next decade. Today, every organization is thinking about productivity and growth. In Canada, we have a very low unemployment rate and difficulty in accessing skilled talent, so we have an opportunity to leverage technology to find ways of doing things differently.

There is something unique happening right now. We see the world taking large language models and how it is being adapted by businesses that are looking beyond consumer use cases for how to improve their business, decrease costs and increase their revenue.

There is immense pressure on businesses to act now or risk falling behind AI-augmented competitors. Are businesses ready for the fast-paced AI adoption?

In Canada, 30% of Canadian companies have actively deployed AI, and nearly half (48%) say their company is exploring AI but has not deployed it into their business operations yet. Companies that adopt AI first to effectively and ethically use the technology to drive revenue and improve operations will have the competitive advantage over those companies that fail to fully integrate AI into their processes.

In the next few years, businesses are likely to scale their AI programs more quickly by looking to areas such as digital labour, IT automation, security, sustainability, and application modernization where AI has begun to make advancements.

Ultimately, success with new technologies in AI will rely on the quality of data, data management architecture, emerging foundation models and good governance. With these elements—and with business-driven, practical objectives—businesses can make the most out of AI opportunities.

Additionally, as AI becomes more pervasive, and adoption accelerates across business, it is critical for leaders to start preparing the workforce for collaboration with AI tools. Canadian executives estimate 42% of their workforce will need to reskill as they adopt generative AI in their business over the next three years. This is a pivotal moment for Canadian business leaders to rethink how they will reskill or upskill their people to work alongside AI. Taking these steps now in Canada is critical to ensure our industries and organizations maintain leadership and are not left behind.

What is IBM doing to help clients gain competitive advantage with AI?

We want to ease current enterprise AI burdens and enable businesses to easily develop, tune, and deploy enterprise-ready and trustworthy AI more easily and at scale. We are helping clients drive productivity across core business processes. We recently established Center of Excellence for generative AI that uses the expertise of more than 1,000 consultants to help businesses make the transition to generative AI.

With watsonx, IBM is helping businesses manage their own AI-supported data and use it at scale in a more trustworthy and open environment, to drive business success. watsonx will also provide organisations with a toolkit to support the governance of AI and ensure data is always secure and complies with regulatory and ethical requirements.

We are creating new opportunities for our clients with our unique ability to integrate technology and business expertise and to co-create with them on digital reinvention.

There is a lot of discussion on ethics, regulation, security when we talk about AI. So, how do you structure and govern these systems? What is the importance of AI governance?

We’re very clear on this. If a company building AI tools can’t state clear principles, they follow to promote ethics and responsibility, or if they don’t have practices in place to live up to those principles - their technology has no place in the market.

We are committed to the responsible stewardship of powerful technologies like AI. That means:

• Principles - making clear that the purpose of AI we build is to augment human expertise, judgement and intelligence - not replace them - and that AI must be transparent, fair and explainable
• Practices - infusing a culture of AI ethics throughout all stages of building and deploying AI systems, and structuring our products - including an entire aspect of our new AI platform - watsonx.governance - to provide precisely the level of explainability and transparency that we feel must be standard in these systems.
• Policies - and, finally, advocating for public policy, including the regulation of AI, that promotes fairness, explainability and transparency, that regulates use cases - where technology actually meets people, and that places the greatest regulatory control on use cases with the greatest risk of societal harm.

At the end of the day, the goal is simple: trust. Our principles, our practices, and the policies we advocate are all focused on promoting trust in AI. Because if it’s not trusted, society will never fully realize its benefits.

What is the biggest opportunity for Canadian businesses when it comes to AI and Hybrid Cloud?

Hybrid cloud and artificial intelligence have clearly become the most transformative enterprise technologies of our time. This fact is evident when we look at the adoption rate of both technologies.

Hybrid cloud has become the most prominent form of IT architecture. We believe that a true Hybrid Cloud Architecture will allow our clients to host workloads wherever they need it without locking them out of innovation. Today, with IBM’s hybrid cloud approach businesses can gain access to all their workloads via a single pane to the right data, apps, tools and resources across public and private clouds, on premise and at the edge.

For companies that are unsure whether their on-site technology infrastructure can handle implementing AI, IBM offers a hybrid cloud solution. It combines on-premises infrastructure with public and private cloud systems, which means almost any business that wants to adopt AI can.

With the combination of our AI stack, cloud technology and industry expertise, IBM is committed to bringing the power of foundation models to enterprise clients and to help them optimize outcomes and responsibly tap into AI to digitally transform. While foundation models can represent a drastic change in how businesses can create and scale AI, few organizations have the skills and infrastructure needed to build or utilize foundation models.