Using AI/ML to optimize your tech stack and enhance business efficiency
In this Help Net Security interview, Arthur Hu, SVP, Global CIO and Services & Solutions Group CTO at Lenovo, discusses how AI/ML is optimizing tech stacks, the hurdles anticipated in its integration, the role of AI in enterprise resilience and agility, and strategic approaches to innovation despite budget constraints. Also, we’ll touch on the evolving role of CIOs and the potential for ‘as-a-service’ offerings to ease tech stack management.
How is AI/ML impacting your tech stack, and what challenges do you foresee in its integration?
Across industries, AI is powering significant improvements in innovation, organizational operations, customer experience, and meaningful business insights. Any organization that does not implement AI into its tech stack is in danger of losing out on the ability to scale, flex, and innovate, eventually dulling its competitive advantage.
At Lenovo, we are exploring AI adoption as part of a wider effort to transform our business operations. One example is how we automate how we deliver to customers. Each of our customer PC orders that our largest global manufacturing base handles each year launches a series of complex tasks across multiple production lines and employee schedules. The planning process for each order used to take six hours, so we had a strong case to optimize it.
Utilizing emerging AI technologies, such as sequential planning algorithms based on deep machine learning, we developed a “decision-making” engine with autonomous learning ability—meaning that the longer it operates, the smarter it becomes.
The result? We cut planning processes from six hours to just 90 seconds. Over the course of a year, that’s a saving of 4.1 million hours! Imagine how many people and how much computing power that is freed up to do more value-added activities for our customers.
As with any technology, AI must be designed thoughtfully, ethically – and regulated properly to ensure it is used responsibly. Another challenge during the integration of AI is the risk of making certain job roles obsolete.
In fact, at Lenovo, we think of it as Augmented Intelligence instead and believe that human intervention and involvement are still necessary. Technology can make processes more efficient which frees up employees’ time to do other things to add value to an organization.
What advice would you give enterprise CIOs wanting to remain resilient and agile in light of the “urgent pressure” to address AI/ML?
CIOs who are typically in charge of innovation now see themselves as responsible for driving their company’s business strategy. In our global study of CIOs this year, 84% of executives surveyed said that their company’s success and failure hinges more on their performance as CIO than other C-Suite roles. This is a telling sign that organizations are looking to AI/ML to drive different aspects of the business, from IT operations to talent recruitment, to CRM.
My advice to CIOs that are about to embark on their innovation journey, is to work with your business partners to define their business goals for innovation and identify the right combination of higher business value, more mature technology, and minor resource that will be needed for success. If we start with the right factors to promote innovation, it’s more likely to succeed within an organization, become recognized as a business imperative, and receive additional funding for future trials and wide scale-out.
In addition to improving engagement with innovation initiatives across an organization, it’s also important to establish a holistic innovation management mechanism that can ensure continuous innovation across different teams. An example could be building platforms/tools and communities on AI/ML to empower engineers. At Lenovo, we’ve established a corporate-wide developer community of about 14,000 engineers for knowledge sharing, collaboration, and capability upgrading. With AI/ML now a part of our tech stack, there has been increasing collaboration with our tech partners, external vendors, and internal domain experts, to build an ecosystem where innovation can grow and flourish.
CIOs can consider taking a short, mid, and long-term approach to innovation when doubling down on investment in R&D for AI, ML, or both. In the short to mid-term, CIOs should set up teams and processes to be able to both experiment with new technologies (whether AI/ML or other), as well as scale up promising technologies.
Over the course of the implementation period, I recommend putting accountability onto the deploying team to ensure that the measurable impact of AI/ML is articulated in a way that can be quantified from a financial perspective. In this way, CIOs can maintain the confidence of internal stakeholders that these investments do add value to the organization and gain their buy-in to continue investing in AI/ML innovation.
What are your recommended strategies to mitigate the impact of insufficient budgets for innovation and digital transformation?
Do not embark without identifying the conditions for success, including budgets. If you believe the budget is insufficient to achieve your business outcomes, you’ll need to realign one or the other – otherwise, you are setting yourself up for failure and wasting both time and effort.
So, it’s important to either make the case for more budget or tweak the target outcomes to fit the given budget. This is where pay-as-you-go solutions can help.
Deploying technology as a service using solutions is one way to respond and strengthen the tech stack when budgets are tight. They enable IT leaders to scale without incurring incremental CAPEX and keep IT infrastructure running smoothly at lower costs.
In what ways are “as a Service” (aaS) offerings aiding CIOs in managing their tech stacks?
As a Service solutions are able to deliver proven, repeatable outcomes on core scenarios, enabling IT leaders to focus on innovation and be more agile in responding to their organizations’ changing needs and investment appetite.
We know our customers need a simple and easy way to use IT – it must more adjustable, cost-effective, and better yet, able to be adopted as a flexible consumption model. Businesses are choosing IT infrastructure and services that are easy to scale up and scale out, and match their specific needs in a more agile manner.
Given that many CIOs have expressed dissatisfaction with their current IT base, what aspects would you focus on improving or replacing if you had the chance?
I would focus on identifying what your critical path is within your company’s context and expectations. While there are no universal answers, based on our latest CIO research, people-focused challenges are gaining traction compared to last year. IT leaders cited issues like managing remote workforces (59%, up 4%) as “extremely challenging” or “very challenging” to address.
Due to the growing demand for hybrid work, CIOs like me are increasingly being tasked to help our organizations manage workforce productivity. COVID-19 added another layer as we had to make sure employees are set up for success and able to be productive while working from home. We had to set up home workstations for our employees almost overnight and manage remote desktops. On top of it all, security was a key priority in safeguarding our companies’ critical data and infrastructure.
Although the pandemic is now behind us, the world has shifted into a permanent hybrid work mode, and companies are still struggling to find customized technologies to address their unique workforce requirements.