Enterprises are looking to AI to boost productivity and innovation, and one-third of organizations with an interest in the technology have hired or are looking for a chief AI officer, according to new research from Foundry, publisher of CIO.com.\n\nFor its AI Priorities Study 2023, Foundry surveyed IT decision-makers who have either implemented AI and generative AI technologies in their organizations, have plans to, or are actively researching them.\n\nTop of those AI priorities for now is generative AI, with 56% of respondents eager to learn more about it.\n\nGreat expectations for generative AI\n\nIT leaders are looking to leverage generative AI across a range of projects, with the majority interested in applying the technology via chatbots and virtual assistants (cited by 56%). Content generation is another key use case for gen AI, cited by 55% of respondents, with industry-specific applications (48%), data augmentation (46%), and personalized recommendations (39%) rounding out the top five.\n\nJust over a quarter of IT organizations (26%) are already using generative AI to create content such as phishing simulations or for writing policies, with another 42% planning to do so within a year. As for software development, where gen AI is expected to have an impact via prompt engineering, among other uses, 21% are using it in conjunction with code development and 41% expect to within a year. The helpdesk is another area ripe for gen AI use, with 17% currently tapping generative AI for IT support and another 45% planning to in a year or less.\n\nGenerative AI will play a large role in employee productivity, according to 58% of respondents \u2014 to the extent that they are starting proofs of concept to test it for themselves.\n\nOpinions are divided, however, on whether those individual productivity boosts will be replicated at the level of the enterprise, or whether organizations will take the opportunity to do the same work with fewer people. For 55% of respondents, generative AI will enable employees to refocus on high value-adding tasks, while 54% say AI capabilities will enable workforce reduction.\n\nOrganizations are preparing for the arrival of generative AI in a number of ways, with 57% of respondents saying they are already identifying use cases, 45% starting pilot programs, 41% training or upskilling employees on it, 40% establishing policies and guidelines.\n\nAround 30% of IT decision-makers are already putting generative AI tools in users\u2019 hands, and 23% say they are testing apps from vendor partners.\n\nSoftware vendors have been busy infusing generative AI into their products. They will be relieved to learn that 55% of respondents agree such products create better business outcomes but dismayed that only 44% say they will pay more for them.\n\nIT decision-makers are already seeing generative AI functionality appear in some of the enterprise apps they use. Where it\u2019s showing up most often \u2014 and also where buyers say they think it will deliver the most benefit \u2014 is in productivity and collaboration tools such as the M365 Copilot Microsoft will release in November, and marketing\/sales software such as Salesforce\u2019s Einstein Copilot. Where they\u2019re not seeing it, and don\u2019t believe it will be of as much benefit, is in their ERP, a finding sure to disappoint SAP, which announced its Joule generative AI assistant in September.\n\nSecurity and privacy concerns\n\nSurvey respondents have some ethical concerns about the use of generative AI, with security and privacy chief among them (both cited by 36%), followed by authenticity and trust (34%), intellectual property (31%), regulatory compliance (29%), bias (27%), and transparency (27%).\n\nData, too, is a concern, with only 34% of respondents confident their organization has the right data and technology in place to enable effective AI.\n\nThe most challenging requirements they face here are the quality and quantity, privacy and ethical considerations, and data variability.\n\nOn the technology side, the most commonly cited factors affecting the integration of generative AI with existing systems are data integration (45%), security and privacy (45%), user experience (34%), training (31%), compatibility (26%) and change management (25%) \u2014 so much the same concerns as with integrating any other new and legacy systems.\n\nHelping the rich get richer\n\nOrganizations are making AI investments to improve employee productivity (cited by 48% of respondents), enable innovation (43%), and gain a competitive edge (41%).\n\nBy almost every measure, larger organizations (those with 1,000 or more employees) are leading the way in terms of AI investment and adoption: Smaller organizations just aren\u2019t keeping up. So, to the extent that AI is a disruptor, it\u2019s one that\u2019s likely to tip things even further in the direction of those in power.\n\nAmong larger organizations, 38% have hired and 29% are seeking data scientists specifically to support generative AI; in smaller organizations those figures are 17% and 30%. The imbalance continues in hiring for other generative AI support roles too: AI chatbot developers are now working in 20% of larger organizations, versus 8% of smaller ones; while for prompt engineers the split is 15% versus 7%. Chief AI officers are at work in 15% of larger organizations and just 6% of smaller ones.\n\nA developing trend\n\nSoftware developers in 37% of organizations are already getting help from generative AI with code generation or completion \u2014 but again it\u2019s the larger ones that are leading the way, with 41% of them using generative AI for software development, versus 33% in smaller organizations.\n\nAmong those not yet using such assisted development tools, 81% expect to in future, although only 34% plan to within the next year; the rest have not set a timeline.\n\nFoundry surveyed 965 IT decision-makers, half of them in North America, one-third in Asia-Pacific, and one-sixth in Europe, the Middle East or Africa. The technology industry was most strongly represented (20%), followed by manufacturing (13%), services (11%), financial services (8%), education (8%), healthcare (6%), and retail, wholesale and distribution (6%).