FINAL WORD
Consolidation and investment in people
The report specifically recognises consolidation of data and AI systems is a priority .
The proliferation of data and AI systems is shown particularly extensive in the survey ’ s largest organizations – those with annual revenue of more than $ 10 billion . Among these , 81 % operate 10 or more of these systems , and 28 % use more than 20 .
The executives interviewed aimed to pare down their multiple systems , connecting data from across the enterprise in unified platforms to break down silos and enable AI initiatives to scale . But the report acknowledges democratization of AI raises the stakes for governance .
As business units and their staff clamor to use generative AI , executives seek assurance that governance frameworks for the technology can provide not only the needed data accuracy and integrity but also adequate data privacy and security . That ’ s probably why 60 % of respondents say a single governance model for data and AI is ‘ very important ’.
• Talent and skills gaps overshadow organizations ’ other data and AI challenges . Asked how their company ’ s data strategy needs to improve , the largest share of respondents ( 39 %) say investing in talent and upskilling the workforce . An even larger share ( 72 %) say it will be “ very important ” to encourage innovation that will help attract and retain talent .
• Lakehouse has become the data architecture of choice for the era of generative AI . Nearly three-quarters of surveyed organizations have adopted a lakehouse architecture with all the rest expecting to do so in the next three years . Survey respondents say they need their data architecture to support streaming data workloads for real-time analytics ( a capability deemed “ very important ” by 72 %), easy integration of emerging technologies ( 66 %) and sharing of live data across platforms ( 64 %). Ninety-nine percent of lakehouse adopters say the architecture is helping them achieve their data and AI goals , and 74 % say the benefits are “ significant .”
Investment in people is acknowledged as unlocking more value from data and AI . The survey showed talent and skills gaps overshadow organizations ’ other data and AI challenges .
When asked where their company ’ s data strategy needs to improve , the largest share of respondents ( 39 %) said investing in talent . The number-one difficulty they face with their data and AI platforms – with 40 % citing this as a top concern – is training and upskilling staff to use them .
“ With data and AI at the forefront of innovation , our report underscores the commitment of C-suite executives to steer toward a transformative future ,” said Laurel Ruma , Global Director of Custom Content for MIT Technology Review . “ Strategic investments , consolidation efforts , and dedication to governance and democratization of AI are not merely choices ; they are imperatives for success .” p
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