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How IBM Consulting takes on projects with its gen AI platform, IBM Consulting Advantage

Katy Ring Profile picture for user Katy Ring January 29, 2024
A deep dive into IBM Consulting's latest generative AI moves.


Many enterprises will require support to adopt gen AI and that is good news for consultancies as it creates business opportunity. For enterprises themselves, the potential good news is that consultancies should be able to demonstrate how they are using gen AI themselves to improve efficiency and quality of output for their clients.

Gen AI should enable skilled consultants to do more with less, to successfully tackle large, complex projects and provide more strategic value. IBM Consulting recently explained how it, as a scale consultancy embedded in a major technology company, is adapting to the disruption gen AI poses to the consultancy business model.

Consultancy with IBM Consulting Advantage and IBM Consulting Assistants

Generative AI can analyse large amounts of data quickly and accurately enabling decisions based on real-time insights, and it makes it easier to identify patterns and trends to support recommendations, all of which is extremely helpful for consultants working on transformation projects. The technology can also be used to tailor existing consultancy assets for individual clients and can automate many tasks thus reducing the consultancy workload.  This capability is a core component of the recently announced IBM Consulting Advantage, which is a services platform that allows for easy, customized access to their portfolio of proprietary methods, purpose-built AI assets and models, and role-based generative AI assistants (IBM Consulting Assistants).  The platform leverages IBM and partner technology.

Matthew Candy, Global Managing Partner for Generative AI within IBM Consulting, explains that IBM Consulting has 21,000 Data and AI professionals who have already created a lot of consulting project accelerators such as prompt libraries, workflow orchestration, pre-built adapters, AI model benchmarks and commercial assets.

Chris Hay, IBM Distinguished Engineer, adds more detail saying,:

We are putting AI acceleration in the hands of all consultants by providing team level access to IBM Consulting Assistants.

IBM Consulting Assistants use generative AI to create role-based digital assistants for consultants across every delivery stage. The AI models are tuned with IBM proprietary knowledge, including benchmarking data, use case libraries and delivery assets. Combined with methods and workflow tools, it puts the expertise garnered from IBM’s 20,000 AI engagements into the hands of every consultant. When combined with IBM Garage (the company’s collaborative engagement model that aligns cross-functional client groups and IBM to track, govern, and maximize value for transformation projects), IBM claims it brings five-to-seven times the value for clients.   

Using IBM Consulting Assistants, consultants can change Large Language Models depending on the project they are working on by accessing My Prompts from the prompt library and sending them to the appropriate model. As Hays comments:

In the development lifecycle, prompts are the new consulting assets to build on each other’s work.

Things can be quickly packaged up into Consulting Assistants. In the demo we saw, the platform was used to rapidly pull together an atomic essay on why IBM and Salesforce are such a good partnership, for example. Assistants can also be used to generate different personas, that can then be asked questions about, say, a client’s planned new product features. 

The IBM Consulting Assistants platform can be extended into other applications. For example, it is embedded into the IBM Garage Experience platform where it can build new strategic initiatives and generate the related value trees to aid analysis of a project. 

IBM Consulting Gen AI projects

Candy says that the gen AI go-to-market motion is via strategy-led engagements where IBM Consulting works with the client to shape vision and value, create a Component Business Model (CBM) heat map, build the roadmap and business case and then realise value at scale. 

IBM Consulting showcased several areas where it is using gen AI with clients. It led with customer services and has found the technology able to enhance omni-channel virtual agents by typically delivering a 60-70% lift in first contact resolution, and a 20-30% reduction in contact center handling. IBM Consulting has also established that gen AI is a very effective assistant for human customer service agents, providing an 80—100% reduction in pre and post call ops, as well as a 30-40% faster new agent ramp-up, amongst other benefits.

In the Accounts Payable area, IBM has partnered with Microsoft to create a gen AI-powered platform to streamline and automate Source-to-Pay processes. The platform can automate the validation of vendor contracts, a process which now takes five minutes as opposed to half an hour; it has created touchless invoice processing with 90% accuracy and 50% cost reduction; and a Co-Pilot has been developed to assist the sourcing expert, vastly reducing the time taken to review a contract.

Francesco Brenna VP and Senior Consultant at IBM Consulting comments that while:

We had made progress in Accounts Payable with Machine Learning, this still took a long time. You can radically reduce time to market with generative AI.

Finally, IBM Consulting highlighted the benefits gen AI brings to application migration and modernization. IBM Fellow A.B. Vijay Kumar showed how the technology can be used to migrate legacy code by extracting business rules and then reviewing the business rules, finally being deployed to generate API specs. All of the prompts can then be packaged as end-to-end assets in Consulting and made available through IBM Consulting Advantage.

My take

As consultancies build their experience in deploying gen AI across various use cases, they have significant value to offer enterprises as they move from pilots to scale projects. For example, IBM Consulting can demonstrate the benefits of using smaller large language models, of taking multi-model approaches on multi/hybrid cloud and of having a governance capability in place.

This is all good to know. Candy is also candid that gen AI will impact IBM Consulting’s commercial models, saying that project delivery will blend “AIshore” with onshore and offshore sourcing approaches. He also suggested the possibility of being able to leave “” behind, embedded in a transformed process or function to support ongoing client requirements.

However, what the market is really wondering is this: won’t the use of gen AI reduce the cost and, consequently, the price of consultancy projects? I suspect the answer is that gen AI moves the market further towards outcome-based value pricing.

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