In 2024, Generative AI takes the spotlight, evolving from a theoretical concept to a practical, business-oriented reality. This shift will particularly manifest in business-to-business (B2B) landscapes, where customised, domain-specific applications of AI take centre stage.
According to IDC FutureScape projections, by 2026, over 80% of generative AI use cases in enterprises will pivot towards tailored models, signifying a departure from standardised solutions to highly specialised solutions. This shift emphasises the critical importance of data security and governance in developing and maintaining these customised AI models.
As organisations strive to address specific challenges, they’ll invest in domain-specific data, leading to the rise of “solution fabrics” that augment the capabilities of generic Generative AI. This transformation urges a reevaluation of traditional AI applications, highlighting their untapped potential for delivering significant organisational value.
As the realisation broadens, progressive businesses will embrace the broad spectrum of available AI technologies and continually invest in establishing a solid data foundation to support a robust portfolio of existing and future AI solutions.
The rise of Generative AI has also sparked significant buzz and a healthy dose of FOMO, elevating AI’s importance to C-level and even Board-level discussions. As Generative AI progresses into its practical phase, it’s crucial to remember: every facet of AI holds significance.
While Generative AI gains traction, traditional AI – already delivering substantial organisational value – remains largely untapped by many. Organisations should explore the wide range of available AI solutions to optimise the speed and scope of their implementation, maximising their benefits.
The author is head of AI at Qlik. Views are personal.
