The insurance business is built on trust. Likewise, AI cannot work without trust; users and consumers have to believe that it\u2019s providing accurate answers based on sound data. But as a new SAS report shows, trust in AI is a tricky subject, with users placing more trust in generative AI than traditional AI but not always investing in the governance to ensure that trust is warranted.<\/p>\n\n\n\n
As the industry enters a year in which many expect AI to produce a spike in business value, insurers face an inflection point: AI adoption is accelerating, but businesses must address questions around governance and data maturity before they can realize its full potential.<\/p>\n\n\n\n
\u201cOur research shows the insurance industry in line with other sectors \u2013 if not slightly ahead of them \u2013 in terms of delivering trustworthy AI,\u201d said Kathy Lange, Research Director of the AI and Automation Practice at IDC. \u201cHowever, when it comes to the level of maturity of AI and data infrastructures, insurers lag behind.\u201d<\/p>\n\n\n\n
\u201cAI is an imperative for businesses, but it\u2019s not a magic pill,\u201d added Franklin Manchester, Global Insurance Strategic Advisor at SAS. \u201cFor AI to generate value throughout the enterprise, it needs to be supported by talented people and fueled with robust, connected data. The insurers who can infuse AI into their existing operations \u2013 and who establish the governance necessary to deliver safe and responsible AI at scale \u2013 will have a competitive advantage for growth, innovation and creating value for their customers.\u201d<\/p>\n\n\n\n
The Data and AI Impact Report: The Trust Imperative \u2013 an IDC report commissioned by SAS \u2013 reveals a number of themes indicating that the insurance industry, at least compared to other sectors, is taking a cautious, deliberate approach to adopting AI:<\/p>\n\n\n\n
Modest overall AI maturity. The report notes that, among the four industries analyzed (the others being government, life sciences and banking), \u201cinsurance presents the most modest profile in terms of both AI and data infrastructure maturity.\u201d Only 7% of insurers consider themselves \u201ctransformative\u201d \u2013 the lowest of all industries. And 14% remain siloed in their data infrastructure, slowing innovation and limiting enterprisewide adoption.<\/p>\n\n\n\n
Conservative investment profile. About 8% of insurers expect to increase their AI spending by at least 20% in the next year, with nearly 60% saying they expect an increase of between 4% and 20%. About one-third said they expected an even smaller increase (3% or less), if not an outright decrease in investment.<\/p>\n\n\n\n
Trust gaps. Only 9% of insurers combine a high level of trust in the technology with strong trustworthy AI capabilities. Over 40% fall into the categories of either underutilization (low trust in reliable systems) or overreliance (high trust in unproven systems).<\/p>\n\n\n\n
Challenges to AI modernization. Over half of insurance respondents (51%) said their organization lacked effective data governance, and the same percentage said their data foundations were not centralized or optimized. Almost as many (44%) also perceived a shortage of specialized AI talent.<\/p>\n\n\n\n
As insurers move toward AI maturity, expect to see them focus on the uses that generate the most value \u2013 which are those that drive growth. The study found that cost-reduction measures produce the lowest return of any AI use. The bigger opportunities include improving customer experience, expanding market share and strengthening resilience.<\/p>\n\n\n\n
\u201cMaking processes more efficient is still important,\u201d said Manchester. \u201cBut the most competitive insurers will focus on using AI for innovation to drive premium growth through outstanding customer experiences.\u201d<\/p>\n","protected":false},"excerpt":{"rendered":"
The insurance business is built on trust. Likewise, AI cannot work without trust; users and consumers have to believe that it\u2019s providing accurate answers based on sound data. But as a new SAS report shows, trust in AI is a tricky subject, with users placing more trust in generative AI than traditional AI but not …<\/p>\n","protected":false},"author":2,"featured_media":85699,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2],"tags":[672],"class_list":["post-85698","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news","tag-sas-3"],"yoast_head":"\n