EDITOR ’ S QUESTION

The future of enterprise AI isn ’ t about more data – it ’ s about the right data . When AI is grounded in a company ’ s own data , it delivers more useful results and ultimately drives greater trust and adoption .

Only by consolidating their data will companies be able to fully understand the complete customer journey . A trusted data foundation and integrating AI into workflows across the enterprise are key ingredients needed for AI success . Deploying these together , companies can unlock enterprise deployments at scale and drive measurable outcomes from AI automation , personalisation and performance optimisation , including higher sales productivity , faster customer service resolutions and higher-conversion marketing campaigns .

Building a trusted data foundation

For AI to live up to the hype , Large Language Models ( LLMs ) must be grounded in trusted enterprise data . However , with data trapped in disconnected silos , wholesale Digital Transformation and value realisation remains elusive . Prospects are worse when the data being used to ground AI models is incomplete , incorrect or irrelevant – leading to inconsistent , incorrect results . Unlocking the power of trapped data enables better analysis , decision-making and AI automation , grounding customer and business data and metadata – a common language that integrates all applications – in ways that deliver trusted , outcome-oriented results without expensive model training .

Take , for example , real-time data that a prospective customer has just visited a company ’ s website . Previously , sales reps would have had no way of knowing this without manually pulling data into a custom report . Realtime data brings actionable insights , allowing for immediate customer engagement , resulting in higher conversion rates , revenue growth and customer satisfaction . Trust is a key component of successful enterprise AI deployments . By unifying and cleansing their data , companies can ensure that AI models operate on the most accurate information .

Integrating AI into the flow of work

The need to deliver AI in the flow of where companies ’ sales , service , marketing , commerce , developer and other employees work explains why they ’ re leaning into conversational assistants , for their employees to interact with any data or workflow across their enterprise . With specific customer data , employees can generate useful responses which are automatically grounded in all of their organisation ’ s trusted data and metadata . From generating customer campaigns , to answering service questions , everything is personalised , based on consolidated data – all securely within the confines of their company ’ s data and business processes . The powerful combination of data and CRM makes these personalised customer experiences possible . For today ’ s consumer , milliseconds matter . The cost of not keeping up with them could be lost sales opportunities , poor social media reviews , or a disconnect in healthcare delivery . While Generative AI is still in its early stages for most companies , the potential for true enterprise transformation is immense . Those that can put in a foundation of data and trust , and offer AI in the flow of where their employees work , will be able to shift from pilot to production and realise tremendous value , employee satisfaction , customer loyalty and business growth . www . intelligentcxo . com

25