IBM drives enterprise change through innovation in both AI and quantum

Recently, I attended IBM’s Think conference in Boston. The conference is IBM’s space to share with customers the evolution of their products, solutions…and thinking. The show was incredibly well attended including a steady buzz on the expo floor.

The announcements at the show were interesting, however the conversations that ensued outside of the announcements were even more interested. I had the opportunity to talk with several of IBM’s leaders including Chairman and CEO Arvind Krishna, IBM SVP, Software and Chief Commercial Officer Rob Thomas and IBM Head of Research and Fellow Dr. Jay Gambetta. The work IBM is pursuing impacts enterprises today and into the future. Let’s dive in.

The three drivers for IBM

CEO Krishna kicked off the opening key with his typical insightful style focused on three thrusts: AI-first enterprise, hybrid cloud and quantum. These three topics would come up repeatedly throughout the conference. In a way, these three represent a focus for IBM, but also a consolidation of what matters for IBM and their customers moving forward. The bulk of the announcements fall into supporting these three drivers for IBM.

Arvind made the case that “leverage has to be fit for purpose” and “technology is as strategic as finance and defense”. What’s interesting about these statements is how enterprises need to look beyond the generic use of technology and how to use it in a way specific to their organization that changes the trajectory of their efforts. IBM’s perspective is that we are beyond the days of simply using tools and look at how they are leveraged to change the velocity of our organizations.

The statements are both subtle and bold at the same time. Regardless, CIOs must take these seriously. Forward-thinking, business-oriented transformational CIOs are already heading down this path. Traditional, technically oriented CIOs are going to need to shift gears quickly in order to ensure their org does not fall behind. Time is not their friend. Acceleration is the key.

One customer on stage, Aramco, talked about their use of AI and boldly stated that they are “not interested in PoCs” they (Aramco) “want to bring ideas from the lab to the field”. It’s a point about leveraging technology but also accelerating the process.

Key Announcements

• IBM Bob: Once you get beyond the really cute image of Bob, Bob was one of the biggest announcements at Think. There are already 12k licenses of Bob in use today. Bob is an AI-enabled tool that provides developers with the ability to accelerate their development processes using agentic processes.
• IBM Concert: Concert is now a platform that brings together IT operational data moving from insights to actions. The Concert platform includes a number of tools from observability and optimization to protect and beyond.
• IBM watsonx Orchestrate: As enterprises delve further into building and operating agentic workflows, watsonx Orchestrate is IBM’s solution to manage and orchestrate agentic workflows.
• IBM Sovereign Core: Sovereignty is a quickly growing concern among global enterprises as they navigate the increasingly complex landscape of regulatory and compliance requirements from jurisdiction to jurisdiction. Sovereign core provides three aspects: Visibility to compliance state, the ability to control action and the ability to act should issues arise.

IBM Software

IBM’s acquisitions over the past year of both Confluent and Hashicorp are quickly being integrated into the IBM software portfolio. For example, Hashicorp’s Vault is now IBM Vault. It appears that IBM has accelerated the speed in which they are integrating solutions. That is a good move for customers that creates a clear direction of how the products will interoperate.

The emphasis on being an ‘AI-first’ enterprise versus ‘AI-augmented’ came up in several different ways. Arvind talked about the importance of enterprises to consider their relevance. IBM is doing quite a bit of work in AI to help enterprises with this process.

I asked Arvind what he is discussing with fellow CEOs regarding AI. He said, “there is a dichotomy between FOMO and concern about risk.” His recommendation is to “stop worrying about risk and focus on 1-2 things that have strong functional leaders and put whatever resources are necessary for success. Not 10. Don’t pick the ones that are most technically knowledgeable with AI.”

The dichotomy between AI or not is coming up again. For example, Arvind mentioned that half of colleges are penalizing students for using AI while the other half is penalizing for not using AI. 

The combination of these challenges and opportunities is causing a number of challenges for companies like IBM that have solid software products but fighting headwinds in the market from these polar opposite perspectives.

For example, IBM is only one of a very small number of enterprise vendors that truly talks about governance in a way that addresses the challenges for enterprises. IBM’s watsonx.governance product is squarely positioned to address some of these challenges with AI. At the same time, governance is one of the leading hurdles for CIOs to overcome before they are comfortable before moving AI into more sensitive spaces.

Quantum

Speaking of forward-thinking, I had an opportunity at Think to dig deeper into IBM’s quantum efforts. Bottom line is that IBM’s efforts are accelerating and CIOs need to take note.

Quantum is not new and quite a bit of work has already been done to progress the technology and make it more accessible. There is also quite a bit of confusion and misinformation about what quantum is and isn’t. For example, many believe that quantum will replace classic computing as it is ‘just a faster computer’ when compared with the current computing landscape. That’s not true as quantum computing is very different from what we know today as ‘classic’ computing. Each of the two computing types are best suited for different purposes.

Lighthouse customers like Cleveland Clinic are already working with IBM’s quantum computers to solve complicated biology problems.

In my conversations with the IBM team, they have found that quantum is a good solution for solving four types of complicated problems that classic computers struggle with: 

• Chemistry in nature: Creating a digital twin of the real world and mapping how nature operates. Companies with building materials are using quantum to understand model properties and model their products in nature. Chemistry is also a solid use case.
• Optimization: Financial services organizations are looking at ways to optimize as there is a lot of money on the table in doing so. For example, predicting or calculating an underlying portfolio under constraints. The problem has more to do with the constraints that cause greater issues than the number of variables. 
• Engineering Simulation: Calculation of partial differential equations. Think flow in a pipeline, chip design routing or airflow over an airplane. Today, airplane designers are still using wind tunnels.
• Machine Learning: This is the easiest to talk about, but hardest in reality. Most machine learning in classic systems is based off finding patterns. However, some patterns do not have structure. Quantum provides the ability to find patterns in data that classical computing would otherwise not find.

There is also post-quantum cryptography or PQC that is coming up with quantum discussions. More on that in a future post.

IBM Research

My conversations with the IBM Research team over the past year have been very insightful and encouraging. Today, IBM Research is focusing on four key areas: AI, silicon, quantum and mathematical algorithms. At Think I had a chance to engage with the team to understand a bit more about what they’re working on. 

IBM is one of the few enterprise technology companies left with a discrete research division. The combination of the four areas they are focused on solves big problems for enterprises both today and into the future. It’s kind of mind blowing to hear some of the projects they’re currently engaged with. Examples include fault-tolerant algorithms, fault-tolerant quantum, building 1Mw systems (Starling), and improvements in silicon.

CIO Perspective

IBM is doing well to provide end-to-end solutions based on a) how the market is progressing with AI from observability to insights. IBM continues to flesh out their watsonx platform along with new solutions like Concert as enterprise look for ways to automate their processes beyond simple process automation.

Between IBM’s Research division, their existing commercial products and future acquisitions, IBM is working to solve big problems that are facing all of us today and into the future.

One area of note is governance. IBM is one of the few enterprise companies talking about governance for AI…and has a product to address it (watsonx.governance). Governance is one of the key hurdles facing CIOs and holding them back from large-scale AI deployment. To be fair, governance with AI gets complicated very quickly.

Overall, IBM has been making good progress on their solutions, research and acquisitions. The next year will be interesting to watch as they a) progress with adoption of their technology and b) continue to leverage IBM Research in both discovery and commercialization.