The true value of Artificial Intelligence in today's businesses is not determined by the quantity of data available, but by whether that data is structured, coherent and supported by a business context that enables sound decision-making.
This was the central message of the presentation delivered by Bhupendra Patel, Director of Solution Engineering for Data & AI, EMEA Growth Markets at Salesforce, during the 5th Digital Cyprus Conference 2026, organised by CITEA and IMH.
Patel emphasised that organisations today possess vast volumes of data, yet most of it remains fragmented and disconnected, without a unified framework for utilisation. As a result, AI delivers business value only when data is transformed into reliable context capable of supporting autonomous digital agents in decision-making.
He also stressed that, without a unified data architecture and robust governance, artificial intelligence applications may lead to inaccurate conclusions, reduced reliability and increased business risk.
Patel highlighted the transition towards the era of the Agentic Enterprise, in which digital agents take responsibility for end-to-end workflows and operate as active members of the organisation, anticipating needs and executing processes with greater speed and accuracy.
Presenting examples from the market, he noted that the first implementations of these models are already delivering tangible results, significantly accelerating sales cycles and improving customer service through automated processes.
However, Patel pointed out that the majority of organisations continue to face significant implementation challenges. The primary obstacle is not the technology itself, but the gap in business context, insufficient infrastructure and the absence of mature data governance mechanisms.
"Ninety per cent of the work is about operations, not code," he remarked, emphasising that the real challenge lies not in experimentation but in the continuous evaluation, testing and optimisation of systems in real-world environments.
According to the data Patel presented, a significant proportion of data executives have reached incorrect business conclusions due to a lack of context, while many organisations still do not fully trust the outputs generated by AI systems. At the same time, considerable amounts of working time are lost every day on data cleansing and data discovery processes, reducing overall productivity.
To address these challenges, Patel presented a four-layer architecture that connects the engagement, agency, work and context layers, creating a unified real-time data ecosystem.
In closing, he warned that without rigorous and mature governance, data ceases to be a strategic advantage and instead becomes an operational risk for the organisation. As he concluded, the success of artificial intelligence depends not on the models themselves, but on the quality of the context in which they operate.
(Source: InBusinessNews)
