Generative AI to become enterprise cornerstone by 2025
Generative Artificial Intelligence (AI) is poised to become a transformative force across various industries over the next few years, according to insights from technology firms such as DataStax, Rayven, AvePoint, and Diligent. These insights reveal both the burgeoning potential and the complexities anticipated in the forthcoming wave of AI implementation.
Ed Anuff and Davor Bonaci from DataStax predict a significant shift in 2025, moving from AI being a hyped technology to it becoming a fundamental component of real-world applications. The focus will be on sectors such as customer engagement, healthcare, and industries requiring complex decision-making processes. Advancements in generative AI tools are expected to facilitate robust deployments, signalling a transition from experimentation to active deployment strategies by companies. This evolution resonates with previous technological waves, such as the mobile and social media revolutions, where broad enterprise adoption took a couple of years post-launch.
Anuff mentions the necessity of supporting technologies such as vector data embeddings and search, which are becoming refined and widely adopted. This technological maturation is expected to push generative AI into production-ready applications by 2025. Industries like customer service and healthcare, where AI can mitigate cognitive burdens and enhance efficiency, are set to benefit significantly from this shift.
However, integrating AI into business operations is not without its challenges. As highlighted by Rayven's Co-Founder and CEO, Jared Oken, businesses will come to recognise AI as an offering beyond mere productivity enhancement, necessitating an understanding of real-time data handling and advanced decision-making models. Oken underscores the importance of data platforms capable of integrating and analysing real-time data as critical to the evolution of AI applications in business environments.
Alyssa Blackburn from AvePoint emphasises the importance of trust and transparency in AI-generated outputs, which often face scepticism due to potential inaccuracies. She forecasts that regulatory oversight will become crucial to bridge this trust gap, ensuring AI's accuracy and fostering acceptance of AI-generated content as reliable. Establishing responsible AI use standards and mandatory disclosures are viewed as vital steps to integrating AI seamlessly into organisational strategies.
Phil Lim from Diligent anticipates that 2025 will be a pivotal year for AI, marked by a focus on clarifying the return on investment (ROI) from AI systems and the risks of "AI washing"—overstating AI benefits without substantive results. Lim notes that AI governance frameworks will remain essential, though standardisation may still be in development by 2025. Organisations prepared with robust governance will likely achieve greater success, balancing innovation with the risks associated with rapid AI deployment.
The emergence of AI platforms as a service (AI PaaS) is also noted by Bonaci. Such platforms will become increasingly important as they enable organisations to standardise AI development across multiple use cases efficiently. These platforms provide an infrastructure that facilitates the integration of AI into existing workflows, enhancing both security and operational compatibility.
In conclusion, the coming years will see generative AI evolve from a promising technology to a cornerstone of enterprise digital strategies. With advancements in technical readiness and deployment logistics, organisations across sectors are preparing for what could be a defining period in AI adaptation. The dialogue surrounding AI governance, trust, and technology alignment will be critical in shaping how AI embeds itself into the fabric of enterprise operations by 2025 and beyond.
