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IBM Advice recently unveiled its Generative AI Center of Excellence (CoE), with the goal of advancing Artificial Intelligence (AI) capabilities and capitalizing on the transformative potential of Generative AI for business outcomes. Working in parallel with IBM Consulting’s global AI and automation practice, the CoE comprises a large network of more than 21,000 AI and data consultants who have completed more than 40,000 engagements with enterprise clients.
The company said the primary goals of the Center of Excellence (CoE) include improving customer experiences, transforming core business processes, and facilitating innovative business models.
Center of Excellence (CoE) will leverage IBM’s expertise in enterprise-grade AI, including recently announced IBM wasonx and cutting-edge technology from IBM’s trusted ecosystem of commercial partners to proactively accelerate clients’ business transformations. It will also develop new solutions and resources with customers and partners.
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“Our Generative AI Center of Excellence has over 1,000 consultants worldwide with expertise in Generative AI who help clients increase productivity in IT operations and critical business processes such as HR or marketing, elevate their customer experiences and create new business models,” Glenn Finch, global management, data transformation and technology partner at IBM Consulting, told VentureBeat. “It complements IBM Consulting’s existing data and AI practice and will focus on solving client challenges using the full Generative AI technology stack, including core models and over 50 industry-specific classic machine learning accelerators.” domain”.
Finch added that the CoE has made great strides since its inception, actively collaborating with more than 100 customers and successfully delivering a multitude of projects throughout 2023. Additionally, these initiatives have seamlessly integrated generative AI alongside traditional machine learning AI strategies, exemplifying revolutionary technology adaptability and immense potential.
According to the company, the milestones the CoE has already achieved include providing AI-generated spoken word 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 implementation of generative AI to optimize the customer relationship process at Bouygues Telecom.
Streamlining business workloads through generative AI
A study of IDC extension expects the AI services market to experience substantial growth, from about $36 billion in 2023 to about $65 billion by 2026. However, IBM said it recognized that achieving AI at enterprise scale requires a comprehensive and adaptable approach.
IBM Consulting emphasized that it will follow an open and collaborative approach in designing, building, implementing and managing generative AI solutions. This approach involves integrating multiple models from industry-leading vendors across various cloud platforms.
Additionally, with the cutting-edge innovations of IBM Research and the capabilities of the IBM Garage, it is committed to providing custom solutions tailored to each client’s unique business requirements.
“A recent IBM IBV survey found that executives surveyed expect nearly half (48%) of their organization’s staff to use generative AI to augment their day-to-day operations in the coming year. Our years of experience in AI show us that getting to enterprise AI at scale requires a composable, multi-model strategy and a human-centered, principles-based approach,” Finch told VentureBeat. “It’s also worth noting that we treat customer data as our own and will not monetize it. Unlike many IT system integrators, we will not build baseline models by aggregating data from (multi) customers.”
According to the company, its early use of core models has yielded impressive results, with some customers experiencing a significant 70% speed-up in time-to-value compared to conventional AI methodologies.
“Most of the AI in production today is machine learning, and adoption, while accelerating, has been slow and expensive,” Finch said. “Today, many companies are using AI, but the complexity and cost of building and training new AI models have made it more difficult 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 customers. In addition, the CoE will leverage the power of IBM’s unique AI “advisor” toolkit, seamlessly integrating it into internal operations and customer-centric businesses.
“Emerging use cases are exciting many leaders about the potential of generative AI applications for generating sales presentations or writing emails. But the use cases go further, in recruiting, coding or transforming the service to the effectiveness of agent intent,” he said. needs of every business, companies can empower their team with innovative capabilities such as content creative and coding, content summarization, and research.”
Finch added that the company has seen a dramatic increase in customer interest across various C-suite roles and industries as organizations seek to explore the potential of generative AI to improve productivity, increase employee satisfaction, and unlock new business models.
“In HR, organizations are using generative AI to reinvent their promotion process, resulting in an 85% reduction in required support,” he noted. “THE Masters used generative AI for AI-generated sports commentary to improve fan experience and NASA is collaborating with IBM to build basic AI models to analyze petabytes of text and remote sensing data to streamline the creation of AI applications tailored to specific questions and tasks.”
Ensure responsible and ethical implementation of AI
Finch believes business leaders prioritize trustworthiness and reliability in the AI systems they rely on to aid decision-making and streamline processes. He emphasized that the effectiveness of AI depends on the quality of the input data, as the AI system itself will faithfully replicate any biases present in the data.
“At IBM Consulting, we understand that gaining trust in AI, including generative AI, is a socio-technical challenge that cannot be solved with technology alone. Instead, you have 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 consider the risks and unwanted effects of artificial intelligence applications”.
He said that just as IBM was able to build a hybrid cloud services business using the Red Hat OpenShift platform, IBM Consulting aspires to become the leading consulting services provider for its Watsonx generative AI platform.
The company plans to develop a specialized practice focused on Watsonx while expanding its consulting business in collaboration with strategic partners.
He predicts that foundational models, in particular, will propel us into a new era of AI for business.
“We see an incredible opportunity for AI to transform the fundamentals of how work is done in the enterprise,” Finch said. “The foundational 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 at IBM Consulting, as well as one of the most comprehensive AI and hybrid cloud technology portfolios in the industry, and we are dedicated to advancing the AI enterprise.”
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