We are set to see artificial intelligence (AI) shift from experimental and piecemeal use cases to factory automation levels of productivity. That’s equivalent to the 19th century transition when electricity became available to factories – first it lit them and made working hours longer and safer, then it powered assembly lines and machinery to bring a step change in production.
That’s the view of IBM CEO Arvind Krishna, who spoke to the press from this week’s IBM Think event in Boston, where he predicted a 40% increase in enterprise productivity by 2030, using AI.
At the event, IBM majored on announcements around an agent-based operating environment that it said would enable organisations to develop and run swarms of autonomous agents, but bounded by policy-driven guardrails.
Core to the product offer around agentic AI from IBM are:
Watsonx Orchestrate: A centralised control plane to deploy and govern thousands of AI agents that focuses on auditability and policy enforcement across multi-supplier agent environments.
IBM Bob: A specialised agentic development environment with built-in security and cost guardrails, that includes a “Premium Package for Z” to bring agentic AI to mainframe IBM Z environments.
IBM Concert: An AI-powered operations platform that provides a single pane of glass for infrastructure, network and security, without requiring rip-and-replace of legacy tools.
Concert Secure Coder: An autonomous security agent that identifies vulnerabilities, executes remediation code, verifies the fix, and manages the pull request process.
IBM’s chief commercial officer, Rob Thomas, said Orchestrate is already in use by a number of customers. “We’ve had companies like ServiceNow, Salesforce, Adobe, just to name a few, who have taken their agents, enabled those onto Watson X Orchestrate. Lockheed Martin is federating 80 different data sources using Orchestrate and then building custom agents on top.”
AI in enterprises is [like] a light bulb … it’s useful, but it’s not really redefining how the company runs. The AI operating model is about moving beyond light bulbs to things that are more fundamental to how a company operates Arvind Krishna, IBM
Krishna likened the current phase of AI to previous generations of computing, where debate and competition move from core technologies to how they are orchestrated.
“Take the example of the PC era,” he said. “It began with a debate on the microprocessor. A dozen companies competed, and then one architecture – in that case, x86 – won out. It then very quickly moves to the operating system on top. We can put the foundation models and the models in that category, and you can see right now the amount of money that’s going into the infrastructure layer. The real value in every one of these comes with the applications and the deployment into enterprises and consumer.”
Krishna added: “Think of the difference between the light bulb, which is useful, and the assembly line, which actually changed manufacturing productivity and growth in the world forever.
“AI in enterprises is more of a light bulb. It’s email summaries. It’s document creation. It’s meeting preparation. It’s useful, but it’s not really redefining how the company runs. When we talk about the AI operating model, this is about moving beyond light bulbs to things that are more fundamental to how a company operates, and you can see it in the data.”
According to the IBM CEO, AI will bring productivity gains of up to “40, 50, 60, 70%” and will allow businesses to “take those savings and put them back into R&D and into sales that allow us to drive more revenue”.
The executives also announced the general availability of IBM Sovereign Core, which allows for an on-premise air-gapped IBM environment, but is also deliverable with Dell hardware and graphics processing units (GPUs).
Quantum computing ‘just around the corner’
Krishna also declared quantum computing to be “literally just around the corner” and talked about the Cleveland Clinic, which, he said, can now model a 12,000-atom protein. “That tells you that quantum is no longer a science lab experiment. People are doing real use cases of significant scale,” he said.
“We think the time period is 2028 or 2029, and the reason is quite simple. Right now, these machines have got hundreds of qubits [the fundamental unit of information in quantum computing] and can do thousands of gate operations or compute steps before they begin to get decoherent and fall into a noise,” said Krishna.
“We think those thousands will be in the tens of millions in three years. The moment it is that much – ie three orders of magnitude more compute – we believe [it will] allow people to tackle a lot more real-life problems.”
He added that IBM offers a fleet of quantum computers that clients can access from the cloud and a free level where people can get up to 10 minutes a month.
