From Consulting to the C-Suite: A 16-Year Journey
Hu's path into technology leadership wasn't exactly conventional. He started as a computer science major back when, as he puts it, "computer science was cool" wasn't really a thing yet. After graduating, he moved into business consulting, looking to apply technical knowledge to real-world business problems. Lenovo became one of his clients, and eventually, the relationship evolved from consultant-client to something more permanent.
"I had the right opportunity to move from business consulting and actually delivering technology within a company," Hu explained. He joined Lenovo to focus on business transformation, eventually becoming CIO in 2016. His most recent role expansion came with Lenovo's creation of the Solutions and Services Group, a strategic move to layer services and solutions on top of the hardware portfolio that made the company famous.
It's a significant shift, and it didn't happen by accident.
Why Hardware Alone Isn't Enough Anymore
The move from selling boxes to selling services reflects a fundamental change in what customers actually want. According to Hu, Lenovo kept hearing the same message: customers wanted more than a one-time hardware purchase followed by radio silence for three years until the next upgrade cycle.
"They wanted us to deliver more, and services was a good way to engage them and provide them what they want," Hu said. But there's another driver behind this transformation: agility. Hardware is physical and capital-intensive. You buy a server, you own it forever, whether you need it or not. Services change that equation entirely.
By wrapping hardware in service offerings, Lenovo can offer operational expenditure models instead of capital expenditure. Customers can scale up when demand spikes, scale down when it drops, and only pay for what they use. For businesses navigating uncertain markets and rapid technology shifts, that flexibility has real value. It's the difference between owning a car and using Uber: sometimes you need the flexibility more than you need the asset.
When AI Pilots Fail Spectacularly (And Why)
Here's where Lenovo's AI story gets interesting, because it starts with failure. Around 2015-2016, when AI hype was building momentum, Lenovo launched a pilot project focused on supply chain forecasting. The company ranks in the top 10 globally for supply chain operations according to Gartner, managing factories, networks, and suppliers across the world. Better demand forecasting would mean better planning, less waste, and improved efficiency.
The pilot failed. Badly.
But here's the twist: the technology wasn't the problem. The algorithms worked fine. The infrastructure was solid. The issue was people. Employees were terrified that AI would eliminate their jobs, so they quietly sabotaged the project by feeding poor-quality data into the system. AI models learn from data, so garbage in means garbage out. If the data doesn't reflect reality, the predictions won't either.
"We actually had employees effectively sabotaging the data, because they said: 'I don't want to see this succeed, because if it succeeds, you probably take my job away, or you make me do something else,'" Hu recalled.
The solution wasn't better algorithms or more computing power. It was communication and change management. Once Lenovo realized the problem was emotional, not technical, they sat down with employees and had honest conversations about intent. The goal wasn't job elimination. It was augmentation.
Augmentation, Not Replacement: Reframing the AI Conversation
For Lenovo, the "A" in AI stands for augmentation. The idea is simple: humans remain at the center, and AI serves as a tool to make them better at their jobs. Think of it like an ax or a sewing machine—disruptive technologies that amplified human capability rather than replaced it.
Hu emphasized that complex operations like supply chain management still require human judgment. With thousands of partners, millions of parts, and intricate networks, AI models can identify patterns and make predictions, but humans need to validate whether those outputs match reality. Once employees understood this framework, resistance dropped.
This philosophy applies more broadly to how Lenovo thinks about AI deployment across the company. With generative AI creating waves of hype and fear in recent years, Hu sees the same pattern repeating: extreme predictions about either saving or destroying the world, with confused people stuck in the middle trying to figure out what to believe.
"Once people understand that it's really about augmentation, I think they can reframe it, because then it becomes much less of a you or me versus the machine, who's gonna win?" Hu said. He pointed to historical disruptive technologies like fire, wheels, looms, and steam engines, all of which ultimately created more economic opportunity despite initial disruption.
But Hu offered one critical reframe: AI won't take your job, but someone who knows how to use AI better than you might. If you're hand-knitting clothes and someone else has a sewing machine, the machine doesn't take your job—the person using the machine takes your business because they're more productive. It's about learning to use the tools, not fearing them.
AI Everywhere: From Marketing to Machine Telemetry
So where exactly does Lenovo deploy AI? According to Hu, there's no part of the company it hasn't touched. In marketing, the company analyzes feedback from campaigns across hundreds of millions of global users and impressions. Which ads get clicks? Which lead to purchases? Which generate positive reviews? AI helps parse that massive data volume to better understand customers and serve them more effectively.
Then there's device telemetry. Lenovo machines generate constant data streams about performance: overheating warnings, memory issues, power plug failures. By aggregating this technical data from devices where users have agreed to share it, Lenovo gains insights into how people actually use their products. That information feeds back into engineering and quality improvements.
"That button's in the wrong place, or people seem to really struggle using this feature," Hu explained. "You can't manually analyze that. There's just too much data." AI algorithms cluster patterns at scale, essentially letting customers speak to Lenovo through data rather than direct feedback.
The applications span quality control, engineering, prediction, and pattern recognition across every business domain. It's less about one killer AI app and more about systematically applying AI techniques wherever data and decisions intersect.
Mixed Reality and the Metaverse: Beyond the Hype
Lenovo's innovation strategy extends beyond AI into mixed reality technologies, often grouped under labels like AR (augmented reality), VR (virtual reality), XR (extended reality), or the metaverse. Hu prefers to think about it as mixed reality: blending physical and digital experiences in practical ways.
Lenovo offers the ThinkReality XR platform, an end-to-end solution that includes APIs, software developer kits, and the physical hardware. As a provider of computing, AI, storage, and networking infrastructure, Lenovo supplies building blocks for others to create applications.
One practical use case is industrial training. Instead of spending months in a classroom with physical equipment, technicians can use augmented reality to overlay technical information directly onto complicated machinery. Lenovo uses this internally to train service technicians on complex installations, like supercomputer cooling systems. They also sell these solutions externally for industrial scenarios where field workers need hands-on guidance.
Another application is smart education, where mixed reality creates learning experiences that wouldn't be possible in purely physical environments. The technology generates different possibilities by merging digital information with physical contexts in real time.
Lenovo partners with companies like ThoughtWorks in this space and works with NVIDIA (NVDA) on data storage solutions optimized for mixed reality applications. The partnership addresses the infrastructure challenges of storing and processing the massive data volumes that immersive digital twin and metaverse applications generate.
Blockchain: Following the Problem, Not the Hype
Blockchain is another technology Lenovo has adopted, primarily for supply chain applications. The company uses blockchain with partners to create shared visibility across common transactions, along with traceability and authentication capabilities. It's particularly useful for tracking the sourcing and provenance of supplies as they move through Lenovo's complex global network.
But Hu offered a cautionary tale about blockchain hype. Around 2017, when blockchain fever peaked, suddenly every team at Lenovo wanted to use it for everything. During internal architecture reviews, Hu noticed nearly every project proposal included blockchain.
"This doesn't sound right because it's not possible that it's all the things," he recalled thinking. One team wanted to use blockchain for a marketing database application. When Hu pressed them on why, it turned out a traditional relational database—technology that's been around for 40-50 years—would have solved the problem faster and more effectively.
The lesson? Follow the business problem, not the technology. Blockchain has legitimate use cases where characteristics like immutability, traceability, and distributed verification matter. But it's not fast—blockchain's public nature limits transaction throughput, so it won't work for applications requiring millions of transactions per second. The technology needs to match the problem, not the other way around.
"Technologies need to find their proper use case," Hu emphasized. Lenovo continues exploring blockchain applications, but only where the technology's strengths align with actual business needs.
The Services-Led Transformation Challenge
Despite Lenovo's progress, one major challenge remains: shifting perceptions. Many people still think of Lenovo primarily as "the ThinkPad company from all those years ago." And yes, Lenovo still makes ThinkPads, proudly. But the company has evolved substantially beyond that identity.
The transformation from world-class hardware development to hardware plus software, solutions, and services is massive. Hu compared it to building a new company from scratch, because many capabilities that worked for selling hardware don't translate to selling solutions and services. The sales approach differs, the customer relationship model changes, and the value proposition shifts from one-time transactions to ongoing engagement.
"That mindset, it's really almost like building a new company from scratch," Hu said. It's one of Lenovo's biggest challenges but also its most exciting opportunity. The services-led transformation guides investment decisions and shapes conversations with investors and customers.
The numbers suggest the strategy is working: $20.5 billion in quarterly revenue with 30% coming from AI-related products and services represents substantial progress. Lenovo's ongoing $1 billion investment continues funding initiatives like the AI Innovators program, which has expanded to over 165 solutions from more than 50 partners.
What's Next: Personal AI Twins and Agentic AI
Looking ahead, Lenovo's vision is evolving from smart hardware to intelligent partners. The company is developing agentic AI that can automate complex tasks, with internal projections suggesting potential to double workforce productivity by 2027.
One concrete initiative launching in early 2026 is the "Personal AI Twin," an AI agent designed to orchestrate a user's devices and act on their behalf. Think of it as a personal assistant that understands your preferences, manages your technology ecosystem, and executes tasks without constant supervision.
The AI Innovators program continues expanding, focusing on virtual assistance, smarter prediction algorithms, and more empathetic user interactions. Hu sees this space as particularly fertile for innovation and expects significant announcements coming from these partnerships.
The Broader Picture: Non-PC Growth
When watching Lenovo's trajectory, Hu highlighted two key areas: continued leadership in PCs while aggressively growing the infrastructure business and services and solutions divisions. Those growth areas represent Lenovo's future, even as PCs remain an important part of the business.
The company's partnerships support this expansion strategy. Beyond the AI Innovators program, Lenovo maintains collaborations with major technology providers like NVIDIA (NVDA) for computing infrastructure and mixed reality solutions, ThoughtWorks for application development, and dozens of startups and medium-sized companies bringing specialized capabilities.
It's a long game. As Hu pointed out early in the conversation, AI transformation doesn't happen overnight. Lenovo has been at it for the better part of a decade, starting with small pilots and learning from failures. Some experiments didn't work. Some required multiple attempts. But the consistent thread has been persistence and willingness to learn from mistakes.
The Human Element in Technology Transformation
Perhaps the most valuable insight from Hu's experience is that technology transformation is ultimately about people, not technology. The most sophisticated algorithms can't overcome human resistance. The best infrastructure won't deliver results if employees don't trust the intent behind deployment.
Lenovo's early supply chain AI failure wasn't a technology problem—it was a communication problem. Once the company addressed the human concerns and reframed AI as augmentation rather than replacement, adoption followed. That lesson applies beyond Lenovo to any organization deploying transformative technology.
The fear that AI will take jobs is real and understandable, given historical patterns of technological disruption. But history also shows that disruptive technologies ultimately expand economic opportunity rather than contract it. The challenge is managing the transition thoughtfully, investing in change management alongside technology deployment, and helping people develop the skills to use new tools effectively.
Hu's reframe is worth remembering: AI won't take your job, but someone who uses AI better than you might. That shifts the focus from fear to skill development, from resistance to adaptation. It's a more productive framing for both individuals and organizations.
Building the Future, One Use Case at a Time
Lenovo's transformation from hardware manufacturer to AI-driven solutions provider illustrates how legacy technology companies can reinvent themselves without abandoning their core strengths. The company still makes excellent laptops, servers, and infrastructure. But now those products serve as platforms for services, solutions, and ongoing customer relationships rather than one-time transactions.
The $1 billion investment in AI and the 30% revenue contribution from AI-related products demonstrate that this isn't just strategic positioning—it's material business impact. The upcoming Personal AI Twin launch and expanding AI Innovators program suggest Lenovo sees significant runway ahead for AI-driven growth.
Whether Lenovo successfully completes this transformation remains to be seen. Building new business models while maintaining existing ones is notoriously difficult. Shifting market perceptions takes time, especially when brand identity is strongly tied to specific products. And competition in AI and services is intense, with every major technology company pursuing similar strategies.
But Lenovo has at least one advantage: experience learning from failure. The company's willingness to experiment, fail, learn, and try again with better approaches suggests an organizational culture capable of navigating transformation. And in technology, the ability to learn faster than competitors often matters more than getting everything right the first time.
For investors and industry watchers, Lenovo's evolution offers a case study in how established hardware companies can adapt to a software and services-driven future. The key ingredients appear to be substantial investment, willingness to experiment and fail, focus on augmentation rather than replacement, and above all, attention to the human dynamics that ultimately determine whether technology transformation succeeds or fails.
As Hu put it, technologies need to find their proper use cases. Lenovo is still working through that process, figuring out where AI, mixed reality, blockchain, and other emerging technologies deliver the most value. But with $20.5 billion in quarterly revenue and 30% coming from AI, the company has moved well beyond the experimental phase into real business transformation.
The ThinkPad company has grown up. It just might take a while for everyone else to notice.
