IBM Consulting is using AI to maximize consultants' productivity output. Here's how

The consulting profession is all about human relationships. You listen to leaders, help them define their core challenges, and together, you create a vision for the future: helping more customers, and creating new and better products that advance society. 

Now, generative AI can do more than ever in a much more accessible way, including tasks previously considered only the domain of humans, such as writing code, rapidly summarizing ideas, planning and analysis, and even generating new business ideas. For the consulting profession, like many others, generative AI represents a massively disruptive force. This is an existential moment for consulting, much like the rise of software-as-a-service was for the software industry. It has already begun to change the daily lives of consultants, assisting them and freeing up time for their most important and strategic work – understanding and supporting clients' transformation journeys.  

Here are three key insights IBM Consulting has found as we are transforming our own internal operations and client delivery with AI. 

AI can enhance knowledge and productivity  

AI can support consultants at every stage in a consulting engagement. It can help with strategy and design work, project delivery and technology integration, and running and operating a managed service.

Today, AI helps consultants quickly bring together a wealth of background information about their client's situation and challenges, alongside industry data and similar challenges that others have faced. Imagine an IBM consultant with organizational memory at their fingertips – a knowledge base of trusted sources like benchmarking data across industries from the IBM Institute for Business Value and best practices and insights from tens of thousands of prior delivery projects.

Once consultants have input from AI, they can verify, further analyze, and refine that input to produce initial recommendations for the client that are sharper and grounded in data about what works. The first meeting with a client is not writing problem statements or design prompts,it's building on an already-created set of ideas and progressing faster into discussion, decisions, and co-creation. 

Generative AI can also help with important but time-consuming tasks like creating user personas in the design phase of a project. It can quickly generate personas based on existing user research data that consultants can use as a starting point and eventually refine. It can also provide ideas for draft proposals or reports that consultants can build upon, disagree with, and improve.  These two applications of AI not only support consultants' creativity, but also speed up progress for the client.

AI is further useful in the later stages of a consulting project. For example, AI can give consultants easy access to established corporate performance benchmarks around productivity gains or operational agility improvements that help them determine what to focus on next. By comparing current business performance to these benchmarks, consultants and their clients can have better confidence about which work projects will offer the best returns. AI can even suggest initiatives to pursue, such as specific improvements to customer service processes that benchmarks show can drive better results. Consultants can also leverage AI as an advisor in technology modernization, such as helping with code generation to turn thousands of lines of COBOL programming language into Java.

AI is a tool, but human consultants are still central  

Most consultants would say that their favorite part of the work is people-facing – listening, developing ideas together, and building mutual trust. AI doesn't replace those foundational skills, but makes them even more important than before.

Consultants who are good at understanding their client and their needs, bringing in diverse voices and perspectives, and designing solutions that deliver value quickly, will be able to refine these skills while leaning on AI for more manual and repetitive tasks. And, because some of these tasks will continue after an engagement, an AI-powered digital worker trained to work side-by-side with professionals can continue to add value for the client while allowing the human consultant to move to their next strategic problem.

Transparency is essential

As AI becomes more prevalent, transparency is key to maintaining client trust. Clients expect to see the data sources AI uses to generate recommendations and want to know how bias is mitigated. They also expect transparency about how AI supports a consultant's work output. Trust and transparency when applying technology is a core principle at IBM and is embedded in our methods like IBM Garage, our proven, collaborative methodology to help clients fast-track value creation through innovation. 

We work with clients to define, build, and rapidly scale business transformation to quickly turn ideas into outcomes, all while de-risking clients' investments and tracking business value delivered in real time. This methodology also helps with change management so that users are more likely to buy in and adopt the solutions delivered.

At IBM Consulting, we're transforming our own client delivery methods using IBM watsonx, our AI and data platform that's underpinned by governance tools to build trusted and transparent AI models, as well as technology from our strategic partners.For example, we're building watsonx capabilities into IBM Garage to work smarter and faster on behalf of our clients.

This is a new era of consulting in which the leaders will be separated by deeply human skills in building and sustaining trusted relationships, complemented by AI to drive efficiency and help unleash human creativity. 

Learn more about the future of consulting with AI. 

This post was created by IBM with Insider Studios.