IBM Consulting unveils Centers of Excellence for Generative AI to enable business transformation

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IBM Consulting recently unveiled its Center of Excellence (CoE) for Generative AI, which aims to advance artificial intelligence (AI) capabilities and harness the transformative potential of Generative AI for business outcomes. Working alongside IBM Consulting’s global AI and automation practice, the CoE comprises an extensive network of over 21,000 qualified data and AI consultants who have completed over 40,000 enterprise client engagements.

The company stated that the main goals of the Center of Excellence (CoE) include improving the customer experience, transforming core business processes and facilitating innovative business models.

The Center of Excellence (CoE) will leverage IBM’s enterprise AI expertise, including the recently announced IBM Watsonx and the cutting-edge technology of IBM’s respected ecosystem of business partners, to actively drive clients’ business transformations. In addition, new solutions and assets are developed with customers and partners.

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“Our Competence Center for Generative AI employs over 1,000 consultants worldwide with Generative AI expertise who help customers increase productivity in IT operations and in core business processes such as HR or marketing, improve their customer experiences and develop new business models,” says Glenn Finch, global managing partner, data and technology transformation at IBM Consulting, said at VentureBeat. “It stands alongside IBM Consulting’s existing data and AI practice and will focus on solving client challenges using the entire generative AI technology stack, including base models and 50+ domain-specific classic machine learning accelerators.”

Finch added that the CoE has made significant strides since its inception, actively collaborating with more than 100 clients and successfully completing a variety of projects throughout 2023. Furthermore, these initiatives have seamlessly integrated generative AI into classic machine learning AI strategies, exemplifying this breakthrough technology’s adaptability and immense potential.

According to the company, milestones the CoE has already achieved include bringing AI-generated sports commentary to millions of fans during the Masters; the synergistic combination of Generative AI with IBM Watson to discover new applications of Mitsui Chemicals products; and the strategic use of generative AI to optimize the customer relationship process at Bouygues Telecom.

Streamline business workloads with generative AI

A study by IDC predicts that the AI ​​services market will see significant growth, growing from approximately $36 billion in 2023 to an estimated $65 billion in 2026. However, IBM said it recognizes that realizing AI at enterprise scale requires a comprehensive and adaptive approach.

IBM Consulting emphasized that it will take an open and collaborative approach to designing, engineering, implementing and managing generative AI solutions. This approach integrates multiple models from industry-leading vendors across different cloud platforms.

In addition, the company strives to deliver customized solutions that address each client’s unique business needs using the latest innovations from IBM Research and the capabilities of the IBM Garage.

“A recent IBM IBV survey found that executives surveyed anticipate that nearly half (48%) of the employees at their organization will use generative AI to augment their day-to-day tasks over the next year. “Our years of AI experience tells us that the journey to enterprise AI at scale requires a composable, multi-model strategy and a human-centric, principled approach,” Finch told VentureBeat. “It’s also worth noting that we treat our customers’ data as our own and do not monetize it. Unlike many IT system integrators, we will not create base models by aggregating (multi-)customer data.”

According to the company, the early adoption of base models has yielded impressive results, with certain customers seeing a significant 70% acceleration in time to value compared to traditional AI methods.

“Most of the AI ​​in production today is machine learning, and adoption — while accelerating — has been slow and expensive,” said Finch. “Today, many companies are using AI, but the complexity and cost of creating and training new AI models has made it more difficult to successfully transition AI projects from pilot to production.”

The tools in the CoE’s generative AI technology stack are designed to increase productivity and drive innovation for customers. Additionally, the CoE will leverage the power of IBM’s exclusive AI “Advisor” toolkit and seamlessly integrate it with internal operations and customer-facing efforts.

“New use cases are exciting many executives about the potential of generative AI applications for creating sales documents or writing emails. But the use cases go beyond that and include recruiting, code building or service transformation for agent intent effectiveness,” he said. “By adopting and integrating multi-model generative AI solutions, specifically tailored to each company’s needs, companies can augment their team with innovative capabilities such as creative content and code creation, content aggregation, and search.”

Finch added that the company is seeing a significant increase in customer interest across leadership roles and industries as companies seek to explore the potential of generative AI to increase productivity, increase employee satisfaction and unlock new business models.

“In HR, companies are using generative AI to redesign their promotion process, resulting in an 85% reduction in support needs,” he noted. “The Masters used generative AI for AI-generated sports commentary to improve the fan experience, and NASA is working with IBM to build AI foundational models to analyze petabytes of text and remote sensing data to enable the creation of specialized AI applications make it easier.” Questions and tasks.”

Ensuring responsible and ethical AI use

Finch believes business leaders prioritize the trustworthiness and reliability of the AI ​​systems they rely on to facilitate decision making and streamline processes. He emphasized that the effectiveness of AI depends on the quality of the input data, since the AI ​​system itself faithfully reflects any bias present in the data.

“At IBM Consulting, we know that gaining confidence in AI – including generative AI – is a socio-technical challenge that cannot be solved with technology alone. Instead, you need to look at people, process and technology,” Finch told VentureBeat. “We help clients establish their organizational culture around AI governance and responsible AI, build multidisciplinary and diverse teams, and address the risks and unintended impacts of AI applications.”

He explained that just as IBM has succeeded in building a hybrid cloud services business using the Red Hat OpenShift platform, IBM Consulting is striving to become the leading consulting provider for its generative AI platform, Watsonx.

The company plans to develop a dedicated practice around Watsonx while expanding its consulting business in collaboration with strategic partners.

He predicts that foundational models in particular will lead us into a new era of enterprise AI.

“We see an incredible opportunity for AI to transform the fundamentals of how work is done in the enterprise,” said Finch. “Foundation models will create exceptional customer experiences, bring new types of productivity to core processes such as HR or finance, and create entirely new business models. With our deep technology and IBM consulting expertise, as well as one of the broadest AI and hybrid cloud technology portfolios in the industry, IBM is well positioned to help clients thrive in this new era, and we are dedicated to helping businesses evolve AI.”

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