How does Kyndryl ensure that its workforce remains at the forefront of AI advancements, particularly in the context of mainframe modernisation?
2024 so far has been the year of AI adoption – and surprisingly, the mainframe is on the playing field. Approximately 60% of Australian businesses are in the early or middle stages of AI implementation according to Kyndryl’s recent State of Mainframe Modernisation survey. As more organisations embark on their AI journeys, it’s crucial for our people to be equipped with the skills needed to deliver on customer outcomes, both today and tomorrow. But it is more than just AI credentials needed; it is also skills in other technologies that interact with AI including cloud and mainframe. Kyndryl invests in many areas to help employees upskill, cross-skill and re-skill, including running internal training programs that ensure our experts continue to have the most up-to-date certifications required, as well as knowledge sharing across the 175 countries we service customers in.
As a technology evangelist, how do you approach customer-facing engagements to promote Kyndryl’s AI and generative AI capabilities?
A key part of my role as Kyndryl’s local Chief Technology Officer is to listen to the challenges our customers are facing, understand the strengths and weaknesses of each technology in their IT estate, and help them to navigate the adoption of new and emerging technologies. Being vendor agnostic gives us the ability to meet our customers where they are on their digital transformation journeys and take a cross-practice approach considering all aspects of that journey. AI, including generative AI, is understandably a topic on many customers’ minds, so in this case I work closely with our customer partners, consultants and technical experts to understand the customer’s readiness for the technology, the value it can bring in terms of productivity gains and cost savings, and how it should interact with other technologies such as cloud and cybersecurity.
How is Kyndryl leveraging AI and generative AI to modernise mainframe applications and data assets within hybrid cloud environments?
AI, including generative AI capabilities, are increasingly being used to make the mainframe more agile, efficient, and cloud ready. Last year in our inaugural State of Mainframe Modernisation survey, most respondents highlighted security, performance, and reliability as key drivers for mainframe modernisation, yet this year in 2024, one third of respondents stated a main driver was the opportunity to use AI capabilities on their mainframe data and applications. The most impressive use of AI technology for the mainframe is the automation of processes like code analysis, analysing complex digital pathways through a complex IT estate and optimising workloads. While processes such as these have historically required manual data collection and analysis, generative AI radically improves the productivity of that analysis by eliminating manual work. This enables faster refactoring and modernisation by generating new code and solutions based on the existing environment. This allows organisations to leverage the power of hybrid cloud while preserving the reliability and security of their mainframe environments.
What specific challenges do organisations face when integrating AI into mainframe environments, and how does Kyndryl’s new services address these challenges?
I wouldn’t say ‘integrating’ so much as cooperating – AI technology is used cooperatively with the mainframe platform. But, to your specific question about challenges, in general, I am seeing challenges across two main areas: skills and data.
To understand my full answer, however, I’d like to highlight a nuance in the cooperation of the two. Generative AI is optimising the value of the mainframe and its application in two ways. The first is in the traditional distributed digital process – i.e. the tech stack. This is characterised by several capabilities on different platforms that are chained together to support a business process. Think of mobile banking. The platforms chained together include the phone, the mobile operating system, the network, the app server, the database server, and potentially a payments gateway. In this first nuance, we are inserting generative AI capabilities into that tech stack to bring accretive value to the business process it supports.
The second nuance is a meta-use of generative AI. Specifically, using generative AI to provide support staff with a rapid, deep understanding of how the mainframe applications work. But there’s more! Not only deep understanding, but actual modernisation of portions of that application suite by re-write code – in the language, say COBOL, or reimplemented Java, for example.
So, then, to the integration challenges – existing staff often lack the expertise needed to effectively utilise these cases outlined above.
Turning to the data challenge, many organisations continue to struggle with data hygiene; generative AI compounds this problem as it uses all traditional, structured data as well as new, valuable, pools of data found in email, collaboration chats, video, presentations etc. This is why we work closely with customers to offer a range of AI, and data advisory and implementation services including assessments, innovation workshops and proofs of concept to ensure a robust data architecture is in place to enable future innovation.
How is Kyndryl’s AI-infused Kyndryl Bridge platform helping customers optimise their mainframe estates to thrive in hybrid environments?
Optimising mainframe estates in hybrid environments requires a strategic, holistic approach. Our focus is to help businesses leverage the strengths of their mainframes while ensuring they can seamlessly thrive in a hybrid IT ecosystem.
Platforms such as Kyndryl Bridge that are powered by AI and encourage open integration do just this. It allows us to deliver real-time insights and data-driven recommendations that enable customers to view, manage and orchestrate across diverse technology estates.
Kyndryl Bridge also provides real-time insights and predictive analytics that equip both customers and Kyndryl teams with up-to-date information that informs decision-making, while also enabling us to better anticipate and mitigate issues before they arise. These capabilities optimise performance, allowing organisations to better manage workloads across hybrid environments, and seamlessly integrate mainframe operations with cloud infrastructure—reducing costs and improving efficiency.
How does Kyndryl’s commitment to diversity and inclusion influence its approach to technology innovation and customer engagement?
Look at me! I’m gay and very, very comfortable at Kyndryl. This is because of a rich set of employee resource groups we call KINs (Kyndryl Inclusion Networks) that support equity and diversity for our business and the wider community. And, I speak from personal experience, coming out of the closet materially improved my creativity and productivity; and I have scores of colleagues from all of our KINs that share this experience.
Additionally, Kyndryl’s outreach in the community includes our memberships with Social Traders and Supply Nation which enable us to increase our procurement from social enterprises, small to medium businesses and Indigenous owned entities. This in turn helps our customers benefit from a diverse and sustainable supply chain and access under-represented businesses.
As a services business, people are at the centre of everything we do and it’s important that our workforce reflects the communities in which we operate and paves the way for the next generation of technology professionals. The mainframe profession specifically lacks an age-diverse workforce, as nearly half of the global mainframe workforce is reaching retirement age, yet only 53% of new technology professionals have experience in the technology. In Australia, we’re actively working to reduce this talent deficit through our partnership with Federation University. The program provides students studying IT with paid, hands-on experience learning mainframe and other technologies while helping to solve real customer problems. Many of these students progress into graduate roles with Kyndryl, and the program is a fantastic way of skilling up younger generations in established technologies such as mainframe.
Jim Freeman is Chief Technology Officer (CTO) for Kyndryl Australia and New Zealand. He has been instrumental in designing Kyndryl’s technology practices and establishing capabilities, partnerships, consulting models and market presence, and is currently a technology evangelist for customer facing engagements. Jim is a passionate Diversity Champion for the LGBTQ+ Kyndryl Inclusion Network.
Prior to Kyndryl’s establishment, Jim held the role of CTO for IBM Global Technology Services in Asia-Pacific, where he worked closely with customers to design their journey to cloud. Throughout his career he has held a number of technology and leadership positions at IBM in the United States and subsequently Australia, where he has managed the IT infrastructure of some of the world’s biggest organisations.
