After introducing GenAI solutions for HR and IT, global tech giant IBM has now identified sales and finance as key areas for developing and deploying enterprise GenAI solutions, a senior executive told FE.
The legacy hardware company, which has recently shifted its focus to software and artificial intelligence consulting said it sees significant potential in the enterprise GenAI space and has pinpointed several levers to scale this offering globally.
“GenAI has the most impact for enterprises by helping drive productivity improvement and efficiency improvement. We are helping enterprises by creating domain specific solutions across IT, HR, support, supply chain and procurement,” Ritika Gunnar, general manager, product management for Data & AI, IBM.
IBM has observed strong adoption of enterprise GenAI solutions across three key functions—customer care, HR, and software development—among its clients.
For customer care, IBM helps automate backend workflows, accelerating customer engagement and query resolution. In workforce management, areas such as onboarding, query resolution, and employee separation have been enhanced through GenAI-driven automation. IBM has also launched GenAI productivity assistants for enterprise developers through its Watsonx Code Assistant offering. IBM now plans to extend these GenAI solutions to the sales and finance functions, starting with its own operations.
“We believe in being client zero, which means we are the first adopters. We learn and understand new use cases and become more efficient, which helps create new domains and functions to enter,” Gunnar explained.
Early adoption of IBM’s enterprise GenAI solutions for sales and finance functions has already begun among its clients, she added.
Additionally, IBM is opening up some of its enterprise GenAI products to its partner ecosystem. This approach allows IBM to create domain-specific assistants while enabling ecosystem partners to build on top of these offerings.
She further said that the basic tenet for enterprise GenAI solutions is to help the enterprises’ journey from pilot to production. This includes some key areas of focus and investment for IBM that span across training models for AI, security, and accelerating use cases.
She highlighted the importance of a strong foundation for deploying enterprise GenAI which involves marrying the large language models with the enterprises’ data such that data is embedded in the base code.
“Trust is critical when running and managing AI in enterprise environments,” Gunnar said adding that it is an area of investment that IBM has sharp focus on to ensure regulatory compliance, and robust security for its clients.
“Also, big is not always better. Our fundamental belief is that small language models that are fit to (the enterprises’) purpose are better,” she added.
