“IBM aims to be the end-to-end technology provider for our customers. We want our product portfolios to work together seamlessly. We’re excited about sharing more milestones in the future“
Hi, Bill. Welcome to the Interview Series. Please tell us about your journey in the technology industry and how this industry has transformed in the post-COVID era.
I started my career at PwC as an IT consultant for two years, and then spent another six years at FileNet doing software development and performance analysis. I then joined IBM as a Senior Development Manager and have been here for almost 15 years. I became Vice President of IBM Automation Product Management in August 2021.
Amidst COVID, organizations across all industries came face-to-face with the fragility of their businesses and for many that included acknowledging the brittleness of their businesses. At that time, a lot of effort was put into rebuilding or building infrastructure with an eye toward resilience and adaptability.
Now, in the post-COVID era, we’re seeing businesses refocus on optimizing productivity and efficiency – through this new lens of resilience and adaptability – while maintaining a healthy investment for growth. The ability to achieve this all starts with IT optimization. It’s about creating an infrastructure with the tools a site reliability engineer needs to identify and fix a problem before it even occurs or before it impacts the business.
Today’s IT managers are spending a lot of their time reacting to alerts and are coming to IBM asking for products like Turbonomic and Instana to help them balance high service level agreements and optimization, while being mindful of costs. To compete in the post-COVID era, technology leaders need tools that can identify problems before they become systemic and dynamically resource the applications, they have responsibility for.
You are among the leading influencers in the cloud and AI industries. What inspired you to formulate an AI-centric strategy in 2023?
IBM’s more than decade-long focus on AI has paved the way for our most recently launched capabilities and technologies like watsonx, as well as our thoughtful policies and practices. In particular and in practice, IBM has continually built our AI technology around five keyfocus areas: Explainability, Fairness, Robustness, Transparency and Privacy.
We believe that AI should benefit the many, not just an elite few. And that a culture defined by diversity, inclusion and shared responsibility are imperatives for building and managing AI and delivering real value for both business and society. We recognize though that achieving trustworthy AI at scale is a bigger challenge than any one company can take on. An open and diverse ecosystem is required.
But our work in AI began long before launching Watson in 2011 and now IBM has embraced the next stage of maturity in AI through what we call “foundation models”, which make deploying AI significantly more scalable, affordable, and efficient for enterprises. We’re steadily aiming toward an outcome-based peak in our AI journey that I like to call “the nirvana state of software” — where AI allows people to use technology that gets enterprise work done at an enterprise scale without being experts in how enterprise software works.
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Generative AI has completely taken over all major discussions in terms of investments and budgeting this year. Could you highlight some of your recent works in the genAI domain?
IBM’s always been at the forefront of generative AI, and we’re glad it’s entered the mainstream conversation. For a long time, we’ve thought about how to embed technology that’s predictive in nature, like intelligent automation solutions, into our offerings to help organizations maximize revenue potential and increase productivity.
Most recently, we launched IBM’s Watson Code Assistant at IBM Think, a solution that can help bridge the hybrid cloud developer skills gap by streamlining the process for writing code in a way that increases productivity and unlocks creativity.
IBM Watson Orchestrate is also a solution that we’re very excited about because of its ability to leverage natural language processing to amplify worker productivity across business operations ranging from sales to HR. All of these recent developments have been built within the framework of our goal to help businesses realize value from generative AI.
How are AI journeys influencing business operations?
IBM helps clients apply AI to make their businesses more productive and innovative. For us, this means ensuring our clients can use AI to obtain better information and ultimately, make decisions based on data.
We want to help our clients to use AI to increase operational efficiency and manage costs. Each of IBM’s AI-powered products – including solutions such as IBM Turbonomic, which provides continuous application performance while safely reducing cloud costs, or IBM Hybrid Cloud Mesh, a new offering that delivers simple, secure, and predictable application-centric connectivity for edge, hybrid, and multi-Cloud environments – is developed to help enterprises automate and optimize their business operations to achieve revenue objectives.
Could you highlight some of the best examples of AI-powered digital journeys that IBM has been part of?
Absolutely, a great example comes from within IBM’s office of the chief information officer and the use of IBM Turbonomic.
IBM’s CIO manages a 1,600 strong IT team supporting business applications for more than 280,000 users who need reliable, continuous performance. IBM’s application teams needed to solve the challenge of understanding proper infrastructure resource configurations when deploying a new service—especially with the growth of complexity following the adoption of Red Hat OpenShift.
Turbonomic automatically executed 45,000 actions per month, achieved a 3.8 TB decrease in cumulative memory limits and a 64% decrease in CPU requests. This meant real financial savings and more importantly, minimizing repetitive, tedious tasks that freed team-members up to work on more value additive projects.
IBM also leveraged automation tools in its own HR department in order to free staff to work on strategic value-add projects rather than busywork, such as gathering data from multiple systems. IBM Watson Orchestrate automated 12,000 hours of manual data-gathering and data-entry tasks in one quarter.
The system also helped IBM HR’s quarterly promotion program run efficiently and fairly, pulling data on 17,000 employees from several systems. This process, which used to take 10 weeks now takes five. The HR department could then focus on workforce planning rather than repetitive tasks.
Could you tell us more about Vela and watsonx? Do you plan to integrate the two platforms for better business operational efficiency in the near future?
With each passing year, more complex models, new techniques, and new use cases require more compute power to meet the growing demand for AI. The choices we’ve made with the design of Vela gives us the flexibility to scale up at will and readily deploy similar infrastructure into any IBM Cloud data center across the globe. Vela is now our go-to environment for IBM researchers creating our most advanced AI capabilities, including our work on foundation models and is where we collaborate with partners to train models of many kinds. IBM has deep roots in the world of supercomputing, with a history of designing systems ranked in the world’s top 500 lists. With each system we design, we discover new ways to improve performance, resiliency, and cost for workloads; increase researcher productivity; and better align with the needs of our customers and collaborators.
At Think 2023, we announced watsonx, IBM’s gateway to latest AI tools and technologies on the market today. With watsonx, IBM is offering an AI development studio with access to IBM-curated and trained foundation models and open-source models, access to a data store to enable the gathering and cleansing of training and tuning data, and a toolkit for governance of AI into the hands of businesses that will provide a seamless end-to-end AI workflow that will make AI easier to adapt and scale. Clients will have access to the toolset, technology, infrastructure, and consulting expertise to build their own — or fine-tune and adapt available AI models — on their own data and deploy them at scale in a more trustworthy and open environment to drive business success. Competitive differentiation and unique business value will be able to be increasingly derived from how adaptable an AI model can be to an enterprise’s unique data and domain knowledge.
IBM aims to be the end-to-end technology provider for its customers. To that end, we ensure our product portfolio work together seamlessly and there will be upcoming milestones for integration.
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In the era of AI and automation, do you think companies would look out for key partners such as IBM to meet the demands of Responsible AI and Trustworthy AI?
IBM embeds ethical principles across company’s global operations through an AI Ethics board. The Ethics Board provides centralized governance and accountability while still being flexible enough to support decentralized initiatives across IBM’s global operations. Having worked on an early version of Watson OpenScale, I have first-hand experience with how seriously IBM takes responsible and trustworthy AI.
Please tell us about the tech talent development resources that IBM is currently offering?
IBM is training the workforce through education and talent development programs so they can partner and work effectively with emerging technologies and prepare for jobs of the future.
To help close the skills gap, we offer a range of education, skills, and career readiness programs to students and job seekers at n****** – all grounded in skills and career tracks relevant to the era of AI.
Examples:
- IBM has made a global plan to provide 30 million people of all ages with new skills needed for the jobs of tomorrow by 2030. This commitment will help democratize opportunity, fill the growing skills gap, and give new generations of workers the tools they need to be successful in an ever-changing economy.
- IBM has also committed to invest $250 million in apprenticeships and other New-Collar programs by year end 2025.
What are your observations from the job market associated with AI and data science skills?
We’re seeing employees’ expectations for the workplace shift. Businesses can leverage technological advancements, such as AI, in existing workflows and processes to improve efficiencies. Employees, without any data science or AI skills, can use the power of robotic processing automation and conversational AI tools to increase productivity by automating repetitive tasks, empowering them with time to focus on higher value work and more meaningful interactions. For example, IBM Watson Orchestrate can help optimize HR processes like automating payroll, better managing employee data and automating key hiring and onboarding processes.
What are your predictions on the future of Generative AI and how it would offer a broad range of alternatives to enterprise organizations as well as startups in the Business Analytics domains?
When Generative AI burst onto the scene, it felt to me as if the world advanced 20 years in a week. For the future, I see advancements in how abstract of an ask the AI can recognize.
For example, being conversational, what if you can say, “I need a data scientist,” and the system knew what is needed with just this simple ask? Not only that you need to draft a job description and where it needs to be posted, but also the right skills, experience, and education you need, would all already implicit and understood. I sometimes think of it like a virtual assistant for the enterprise – for users to experience conversational AI with computers that understand intent and automatically put the actions into motion.
That’s the journey we’re embarking on, and I’m thrilled to be at IBM and part of the team charting the frontiers in this rapidly evolving field.
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Softer Questions
Burn the midnight candle or soak in the sun?
Midnight candle
Coffee, or Tea?
Coffee
First memorable experience in your career as a technology leader?
Building my first product that went on to generate well over $100M
One thing you remember about your employee (s):
Honesty, trust, transparency
Most useful app that you currently use:
iHeart Radio
Your favorite AI/ML feature that you want everyone to try out?
“I really can’t wait for more people to try Watson Orchestrate! I use it to automate some of the more mundane, repetitive tasks on my to-do list so I can focus more on parts of my job I really enjoy. It’s been a real game changer for my day-to-day.”
Thank you, Bill ! That was fun and we hope to see you back on cioinfluence.com soon.
[To participate in our interview series, please write to us at sghosh@martechseries.com]
Bill is responsible for product management and strategy of IBM’s Automation portfolio. This includes a range of technologies covering business automation, application integration, IT Automation, and application runtimes all focused on increasing personal and business productivity with automation technology.
Bill has been in the software product management and engineering space for over 20 years holding various roles in IBM engineering & product management ranging from unstructured data/content management, information life cycle governance, business process management, machine learning & AI, as well as cross product disciplines such as performance analysis and capacity planning.
Bill is well regarded in the industry and decades of experience in helping clients deliver technology to mission critical business applications.
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