IBM Consulting introduces Center of Excellence for generative AI to empower business transformation
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IBM Consulting recently revealed its Center of Excellence (CoE) for generative AI, aiming to advance artificial intelligence (AI) capabilities and capitalize on the transformative potential of generative AI for business outcomes. Operating parallel with IBM Consulting’s global AI and Automation practice, the CoE encompasses an extensive network of over 21,000 skilled data and AI consultants who have completed over 40,000 enterprise client engagements.
The company stated that the Center of Excellence (CoE)’s primary objectives include enhancing customer experiences, transforming core business processes and facilitating innovative business models.
The Center of Excellence (CoE) will leverage IBM’s expertise in enterprise-grade AI, including the recently announced IBM watsonx and cutting-edge technology from IBM’s esteemed ecosystem of business partners, to actively expedite clients’ business transformations. It will also develop new solutions and assets with clients and partners.
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“Our Center of Excellence for generative AI has over 1,000 consultants globally with generative AI expertise who are helping clients drive productivity in IT operations and core business processes like HR or marketing, elevate their customer experiences and create new business models,” Glenn Finch, global managing partner, data and technology transformation at IBM Consulting, told VentureBeat. “It stands alongside IBM Consulting’s existing data and AI practice and will focus on solving client challenges using the full generative AI technology stack, including foundation models and 50+ domain-specific classical machine learning accelerators.”
Finch added that the CoE has made significant strides since its inception, actively collaborating with more than 100 clients and successfully delivering a multitude of projects throughout 2023. Furthermore, these initiatives have seamlessly integrated generative AI alongside classical machine learning AI strategies, exemplifying this groundbreaking technology’s adaptability and immense potential.
According to the company, the milestones the CoE has already achieved include the provision of AI-generated spoken sports commentary to millions of fans during the Masters; the synergistic combination of generative AI with IBM Watson to uncover new applications of Mitsui Chemicals products; and the strategic deployment of generative AI to optimize the customer relationship process at Bouygues Telecom.
Streamlining business workloads through generative AI
A study by IDC predicts that the AI services market will witness substantial growth, expanding from approximately $36 billion USD in 2023 to an estimated $65 billion USD by 2026. However, IBM said it recognizes that achieving enterprise-scale AI necessitates a comprehensive and adaptable approach.
IBM Consulting emphasized that it will be following an open and collaborative approach in designing, constructing, implementing and managing generative AI solutions. This approach involves integrating multiple models from industry-leading providers on various cloud platforms.
Furthermore, with the cutting-edge innovations from IBM Research and the capabilities of the IBM Garage, it strives to deliver customized solutions tailored to the unique business requirements of each client.
“A recent IBM IBV survey found that executives surveyed expect nearly half (48%) of the staff in their organization will use generative AI to augment their daily tasks in the next year. Our years of AI experience show us that getting 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 consider clients’ data their own and will not monetize it. Unlike many IT systems integrators, we will not create foundation models by aggregating (multi) clients’ data.”
According to the company, its early utilization of foundation models has yielded impressive outcomes, with certain clients experiencing a significant 70% acceleration in time-to-value compared to conventional AI methodologies.
“The majority of AI in production today is machine learning, and adoption — while accelerating — has been slow and expensive,” said Finch. “Today, many businesses are using AI, but the complexity and expense of creating and training new AI models have made it harder to successfully move AI projects from pilot to production.”
The tools in the CoE’s generative AI technology stack are designed to amplify productivity and drive innovation for clients. Moreover, the CoE will harness the power of IBM’s exclusive AI “advisor” toolkit, integrating it seamlessly into internal operations and client-centric endeavors.
“Emerging use cases excite many leaders about the potential for generative AI applications to generate sales decks or write emails. But the use cases go beyond that, in recruiting, code creation, or service transformation for agent intent efficacy,” he said. “By adopting and integrating multi-model generative AI solutions unique to each business’s needs, enterprises can augment their team with innovative capabilities like creative content and code creation, content summarization and search.”
Finch added that the company has witnessed a notable surge in client interest across various C-suite roles and industries as organizations seek to explore the potential of generative AI in enhancing productivity, boosting employee satisfaction and unlocking new business models.
“In human resources, organizations are using generative AI to reimagine their promotion process, resulting in an 85% reduction of support required,” he noted. “The Masters used generative AI for AI-generated sports commentary to improve the fan experience, and NASA is working with IBM to create AI foundation models to analyze petabytes of text and remote-sensing data to make it easier to build AI applications tailored to specific questions and tasks.”
Ensuring responsible and ethical AI deployment
Finch believes that business leaders prioritize trustworthiness and reliability in the AI systems they rely upon to facilitate decision-making and streamline processes. He emphasized that the effectiveness of AI is contingent upon the quality of input data, as the AI system itself will faithfully replicate any biases present in the data.
“In IBM Consulting, we know earning trust in AI — including generative AI — is a socio-technical challenge that can’t be solved with technology alone. Instead, you need to look across people, processes and technology,” Finch told VentureBeat. “We help clients establish their organizational culture around AI governance and responsible AI, build multi-disciplinary and diverse teams, and consider the risks and unintended effects of AI applications.”
He stated that just as IBM succeeded in establishing a hybrid cloud services business utilizing the Red Hat OpenShift platform, IBM Consulting aspires to become the foremost consulting services provider for its generative AI platform Watsonx.
The company envisions the development of a specialized practice centered around Watsonx while concurrently expanding its consulting business in collaboration with strategic partners.
He predicts that foundation models, in particular, will push us into a new era of AI for business.
“We see an incredible opportunity for AI to transform the fundamentals of how work gets done in the enterprise,” Finch said. “Foundation models will create exceptional customer experiences, bring new kinds of productivity to core processes like HR or finance, and create entirely new business models. IBM is very well positioned to help clients thrive in this new era, with our deep technology and domain expertise in IBM Consulting as well as one of the most comprehensive AI and hybrid cloud technology portfolios in the business, and we’re dedicated to advancing enterprise AI.”
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