The head of IBM Consulting, Mohamad Ali, has stated that consulting firms must fundamentally transform into software companies to remain viable in the era of artificial intelligence. This strategic shift is driven by increasing competition from technology companies and evolving client expectations regarding the implementation of AI.
Ali, who returned to IBM two years ago, is leading a major initiative to reshape the company's consulting division. The goal is to create a "service as a software" business, centered on developing thousands of automated digital agents capable of executing complex tasks for clients with minimal human intervention.
Key Takeaways
- Mohamad Ali, head of IBM Consulting, believes the industry's survival depends on becoming software-centric.
- IBM is developing thousands of automated "digital agents" to deliver consulting services as software.
- The consulting sector faces a period of slow growth, with firms like IBM and Accenture adapting their strategies and workforces for AI.
- Despite client skepticism, Ali argues that the high failure rate of in-house AI projects highlights the need for expert implementation.
- IBM's own use of automation resulted in $3.5 billion in savings, serving as a model for its client offerings.
A New Model for Consulting Services
The traditional role of consultants—advising on restructuring, implementing third-party software, or providing specialized expertise—is being challenged by the rise of AI. According to Mohamad Ali, the future of the industry lies in a hybrid model that heavily integrates human expertise with proprietary software solutions.
"The future of consulting is going to be a hybrid of people plus software — like, a lot of software," Ali said in an interview with the Financial Times. "And I think that consulting companies that can’t do that are going to fall away."
This vision involves creating semi-autonomous agents that can handle a wide range of tasks, from data analysis to process optimization. The primary challenge for consulting firms is not just building these tools but also ensuring that thousands of distinct agents can work together seamlessly for clients.
The Race to Develop Agentic AI
IBM is not alone in this pursuit. Major consulting firms, including Deloitte, KPMG, and McKinsey, are actively developing their own agentic AI platforms. These companies aim to offer clients a suite of ready-to-deploy tools that can be customized to their specific needs.
The competitive landscape is also expanding, with technology companies entering the consulting space. Ali noted that these software-native companies are well-positioned to deliver services digitally through AI agents, intensifying the pressure on traditional consultancies to adapt quickly.
Who is Mohamad Ali?
Mohamad Ali has a deep background in software and technology strategy. He first worked at IBM from 1996 to 2009, where he was involved in growing its analytics software business. Before rejoining IBM, he held senior positions at Hewlett-Packard and served as CEO of a cloud software company. He returned to IBM in 2023 as Chief Operating Officer of the consulting business and has been its head since July 2023.
Navigating a Challenging Market Environment
The push toward AI-driven services comes as the consulting industry grapples with a period of sluggish growth that has persisted for over two years. Firms are betting that helping clients implement AI will reignite demand and open new revenue streams.
For IBM, the consulting division has been the weakest performer this year. It reported no revenue growth, which stands in stark contrast to the 5% growth in its hardware division and 9% growth in software. Ali attributes this slowdown to several factors, including a difficult economy, reduced spending by the U.S. government, and significant in-house AI investments by companies.
Stagnant Growth in Consulting
IBM Consulting's 0% revenue growth this year highlights the broader challenges in the sector. In comparison, IBM's hardware and software divisions grew by 5% and 9%, respectively, indicating a stronger demand for technology products over traditional consulting services in the current market.
Investor and Client Skepticism
While consulting firms are optimistic about AI, some corporate leaders and investors remain cautious. There is skepticism about whether consultants can provide more value than a company's own internal teams when it comes to AI strategy and implementation.
This uncertainty is reflected in the market performance of some major players. Shares in Accenture, a key IBM competitor, have declined by 30% this year. This drop is partly due to investor concerns about how AI will affect its managed services business, which includes outsourced functions like call centers that are ripe for automation.
In response, Accenture CEO Julie Sweet announced that the company is restructuring its workforce for the AI era. This includes plans to reduce staff who are unable to acquire the necessary new skills, underscoring the profound impact AI is having on industry employment.
The Case for Expert AI Implementation
Despite the challenges, Ali is confident that companies will ultimately require the expertise of consulting firms to succeed with AI. He pointed to an MIT study that found a staggering 95% of generative AI projects have so far failed to produce any significant financial returns for the companies undertaking them.
This high failure rate, he argues, demonstrates the complexity of deploying AI effectively and the value that experienced consultants can bring. To prove the concept, IBM Consulting is using its own internal transformation as a key selling point.
"It’s less about the LLMs and now about the applications that you’re building on top," Ali explained, suggesting that the underlying AI models are becoming commoditized, while the real value lies in how they are applied.
IBM has successfully deployed automation across nearly 500 of its own corporate functions. This internal initiative yielded $3.5 billion in savings over a two-year period, providing a powerful example of the efficiency gains possible with agentic AI. This success story forms the basis of IBM's pitch to clients looking to achieve similar results.
