{"id":6313,"date":"2026-03-18T06:02:42","date_gmt":"2026-03-18T06:02:42","guid":{"rendered":"https:\/\/sapidblue.com\/blog\/?p=6313"},"modified":"2026-06-23T09:58:23","modified_gmt":"2026-06-23T09:58:23","slug":"state-of-ai-adoption-insights-from-the-ai-impact-summit-2026","status":"publish","type":"post","link":"https:\/\/sapidblue.com\/blog\/state-of-ai-adoption-insights-from-the-ai-impact-summit-2026\/","title":{"rendered":"State of AI Adoption: Insights from the AI Impact Summit 2026\u00a0"},"content":{"rendered":"Artificial Intelligence is no longer a distant innovation. Across industries, organizations are actively exploring how AI can improve operations, enable better decision-making, and unlock new business opportunities.\n\nTo understand how organizations are progressing on this journey, we conducted\u00a0a short survey\u00a0with booth visitors at the\u00a0<b>AI Impact Summit 2026<\/b>. The survey captured perspectives from\u00a0<b>50 industry professionals<\/b>, including decision-makers, technical evaluators, and AI practitioners.\n\nThe goal was simple: understand\u00a0<b>where organizations stand today in their AI journey, what they want to achieve, and what is slowing them down.<\/b>\n\nThe results reveal an interesting picture of\u00a0<b>AI ambition versus AI execution<\/b>.\n\n<!-- \/wp:post-content -->\n\n<!-- wp:heading -->\n<h2>Where Organizations Stand in Their AI Journey<\/h2>\n<!-- \/wp:heading -->\n\n<!-- wp:paragraph -->\n\nAI adoption is clearly underway, but most organizations are still navigating the\u00a0early stages\u00a0of implementation.\n\nA large portion\u00a0of respondents\u00a0indicated\u00a0that their organizations are currently in\u00a0<b>pilot or proof-of-concept stages<\/b>, while others have moved into\u00a0<b>limited production environments<\/b>.\n\nOnly a smaller percentage reported that AI is\u00a0<b>scaling across multiple functions<\/b>\u00a0within their organization.\n\nThis suggests that while AI experimentation is widespread,\u00a0<b>enterprise-wide AI deployment is still evolving<\/b>.\n\nMany companies are testing use cases,\u00a0validating\u00a0value, and building internal capabilities before committing to broader AI adoption.\n\n<img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/sapidblue.com\/blog\/wp-content\/uploads\/2026\/03\/Group-1000004229-1024x591.png\" alt=\"\" width=\"1024\" height=\"591\" \/>\n\n<!-- \/wp:paragraph -->\n\n<!-- wp:heading {\"level\":3} -->\n<h3>What Organizations are Trying to Achieve with AI<\/h3>\n<!-- \/wp:heading -->\n\n<!-- wp:paragraph -->\n\nWhen asked about their primary AI\u00a0objectives, the responses highlight a strong focus on\u00a0<b>operational improvements and smarter decision-making<\/b>.\n\nKey\u00a0objectives\u00a0include:\n<ul>\n \t<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"1\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\">Decision intelligence and analytics<\/li>\n \t<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"1\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"2\" data-aria-level=\"1\"><a href=\"https:\/\/sapidblue.com\/intelligent-process-automation\" target=\"_blank\" rel=\"noopener\">Process automation<\/a><\/li>\n \t<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"1\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"3\" data-aria-level=\"1\">Risk and compliance management<\/li>\n \t<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"1\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"4\" data-aria-level=\"1\">Enhancing product features with AI<\/li>\n<\/ul>\nInterestingly,\u00a0a number of\u00a0respondents\u00a0indicated\u00a0that their organizations are\u00a0<b>still evaluating potential AI use cases<\/b>, suggesting that many companies are still exploring where AI can create the most value.\n\nThis reflects a broader industry trend where AI adoption is often driven by\u00a0<b>specific business problems rather than technology experimentation alone<\/b>.\n\n<img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/sapidblue.com\/blog\/wp-content\/uploads\/2026\/03\/Group-1000004239-1024x558.png\" alt=\"\" width=\"1024\" height=\"558\" \/>\n\n<!-- \/wp:paragraph -->\n\n<!-- wp:heading {\"level\":3} -->\n\n<!-- \/wp:heading -->\n\n<!-- wp:paragraph -->\n\n<!-- \/wp:paragraph -->\n\n<!-- wp:image {\"id\":2177,\"sizeSlug\":\"full\",\"linkDestination\":\"none\",\"align\":\"center\"} -->\n<figure><\/figure>\n<!-- \/wp:image -->\n\n<!-- wp:heading -->\n<h3>What is Slowing AI Adoption<\/h3>\n<!-- \/wp:heading -->\n\n<!-- wp:paragraph -->\n\nDespite the growing interest in AI, several barriers continue to slow down large-scale implementation.\n\nThe most\u00a0common challenges\u00a0identified\u00a0in the survey include:\n<ul>\n \t<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"2\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\">Infrastructure and performance limitations<\/li>\n \t<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"2\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"2\" data-aria-level=\"1\">Uncertainty around ROI and measurable value<\/li>\n \t<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"2\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"3\" data-aria-level=\"1\">Talent and skill gaps<\/li>\n \t<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"2\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"4\" data-aria-level=\"1\">Security and compliance requirements<\/li>\n<\/ul>\nThese findings highlight a key reality of enterprise AI adoption: success depends not only on algorithms but also on\u00a0<b>data infrastructure, governance, and organizational readiness<\/b>.\n\nMany organizations struggle to move beyond pilot stages because scaling AI requires\u00a0<b>robust data pipelines, integration with existing systems, and clear performance metrics<\/b>.\n\n<img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/sapidblue.com\/blog\/wp-content\/uploads\/2026\/03\/Group-1000004231-1024x533.png\" alt=\"\" width=\"1024\" height=\"533\" \/>\n\n<!-- \/wp:paragraph -->\n\n<!-- wp:heading {\"level\":3} -->\n<h2>Data Readiness for AI at Scale<\/h2>\n<!-- \/wp:heading -->\n\n<!-- wp:paragraph -->\n\nOne of the most revealing insights from the survey was related to\u00a0<b>data infrastructure readiness<\/b>.\n\nA majority of\u00a0respondents reported that their organizations are either\u00a0<b>not fully prepared or only partially prepared<\/b>\u00a0to support AI initiatives at scale.\n\nOnly a small percentage\u00a0indicated\u00a0that their data infrastructure is\u00a0<b>fully AI-ready<\/b>.\n\nThis finding reinforces\u00a0an important point:\u00a0<b>data readiness is often the foundation of successful AI adoption<\/b>.\n\nWithout clean, accessible, and well-structured data, even the most advanced AI models struggle to deliver meaningful business outcomes.\n\n<img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/sapidblue.com\/blog\/wp-content\/uploads\/2026\/03\/Group-1000004233-1024x486.png\" alt=\"\" width=\"1024\" height=\"486\" \/>\n\n<!-- \/wp:paragraph -->\n\n<!-- wp:heading {\"level\":3} -->\n<h2>How Organizations Measure AI Success<\/h2>\n<!-- \/wp:heading -->\n\n<!-- wp:paragraph -->\n\nWhen it comes to measuring the success of AI initiatives,\u00a0<b>operational efficiency<\/b>\u00a0emerged\u00a0as the most common metric.\n\nOrganizations are looking at AI\u00a0as a way to:\n<ul>\n \t<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"3\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\">Improve productivity<\/li>\n \t<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"3\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"2\" data-aria-level=\"1\">Automate repetitive tasks<\/li>\n \t<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"3\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"3\" data-aria-level=\"1\">Reduce manual effort<\/li>\n \t<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"3\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"4\" data-aria-level=\"1\">Enhance decision-making accuracy<\/li>\n<\/ul>\nSome organizations also measure AI impact through\u00a0<b>revenue growth or decision accuracy<\/b>, while a smaller segment is still\u00a0<b>defining their success metrics<\/b>.\n\nThis reflects the evolving nature of AI adoption, where organizations are still learning how to quantify the value generated by AI initiatives.\n\n<img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/sapidblue.com\/blog\/wp-content\/uploads\/2026\/03\/Group-1000004234-1024x577.png\" alt=\"\" width=\"1024\" height=\"577\" \/>\n<h2>How Organizations\u00a0are Building AI Solutions<\/h2>\nThe survey also explored how organizations approach AI development.\n\nThe most common approach is a\u00a0<b>hybrid model<\/b>, combining\u00a0<b>in-house development with third-party platforms<\/b>.\n\nThis strategy allows organizations to:\n<ul>\n \t<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"4\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\">Maintain control over core capabilities<\/li>\n \t<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"4\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"2\" data-aria-level=\"1\">Accelerate development using existing platforms<\/li>\n \t<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"4\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"3\" data-aria-level=\"1\">Integrate AI solutions into their existing technology stack<\/li>\n<\/ul>\nPurely\u00a0third-party approaches were less common, suggesting that many organizations prefer\u00a0<b>a balance between customization and speed<\/b>.\n\n<img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/sapidblue.com\/blog\/wp-content\/uploads\/2026\/03\/Group-1000004235-1024x577.png\" alt=\"\" width=\"1024\" height=\"577\" \/>\n<h2>Expected Timeline for AI Deployment<\/h2>\nAnother interesting insight relates to\u00a0<b>AI deployment timelines<\/b>.\n\nA\u00a0significant number\u00a0of organizations reported having\u00a0<b>active AI projects already underway<\/b>, while others expect implementation within the next\u00a0<b>three to twelve months<\/b>.\n\nAt the same time, some organizations are still in the\u00a0<b>exploration phase<\/b>, assessing potential use cases before committing to development.\n\nThis\u00a0indicates\u00a0that while AI adoption is accelerating, organizations are progressing at\u00a0<b>different speeds depending on their industry, data maturity, and internal capabilities<\/b>.\n\n<img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/sapidblue.com\/blog\/wp-content\/uploads\/2026\/03\/Group-1000004236-1024x506.png\" alt=\"\" width=\"1024\" height=\"506\" \/>\n<h2>About the Survey Respondents<\/h2>\nThe survey responses came from professionals across a variety of industries, company sizes, and roles involved in AI initiatives.\n<h3><b>1. Industries represented include:<\/b><\/h3>\n<ul>\n \t<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"7\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\">Information Technology<\/li>\n \t<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"7\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"2\" data-aria-level=\"1\">Finance<\/li>\n \t<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"7\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"3\" data-aria-level=\"1\">Retail and Ecommerce<\/li>\n \t<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"7\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"4\" data-aria-level=\"1\">Healthcare<\/li>\n \t<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"7\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"5\" data-aria-level=\"1\">Entertainment and Media<\/li>\n \t<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"7\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"6\" data-aria-level=\"1\">Real Estate<\/li>\n<\/ul>\nThe majority of\u00a0respondents came from\u00a0<b>technology-focused organizations<\/b>, reflecting the strong role that the tech sector continues to play in driving AI innovation and experimentation.\n<h3><b>2. Company size<\/b><\/h3>\nRespondents\u00a0represented\u00a0a mix of organizations ranging from\u00a0<b>early-stage startups and small teams to larger enterprises<\/b>,\u00a0providing\u00a0a diverse view of how AI adoption varies across company sizes.\n<h3><b>3. Roles in AI decision-making<\/b><\/h3>\nParticipants also\u00a0represented\u00a0different levels\u00a0of involvement in AI initiatives, including:\n<ul>\n \t<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"8\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\">Final decision-makers<\/li>\n \t<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"8\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"2\" data-aria-level=\"1\">Strong influencers in AI strategy<\/li>\n \t<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"8\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"3\" data-aria-level=\"1\">Technical evaluators<\/li>\n \t<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"8\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"4\" data-aria-level=\"1\">Professionals researching AI solutions<\/li>\n<\/ul>\nThis mix of roles provides insight not only into\u00a0<b>organizational AI adoption<\/b>, but also into how AI decisions are evaluated and implemented across\u00a0different levels\u00a0within a company.\n\n<img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/sapidblue.com\/blog\/wp-content\/uploads\/2026\/03\/Group-1000004240-1024x452.png\" alt=\"\" width=\"1024\" height=\"452\" \/>\n<h2>Bridging the AI Execution Gap<\/h2>\nThe insights from the AI Impact Summit reveal a consistent pattern.\n\nOrganizations are increasingly interested in AI, but many are still working to move from\u00a0<b>experimentation to scalable implementation<\/b>.\n\nThe journey from AI pilots to enterprise-scale deployment requires more than technology alone. It requires the right\u00a0<b>data architecture, development approach, and integration strategy<\/b>.\n\nAt\u00a0<b>SapidBlue<\/b>, we help organizations navigate this transition by designing and building scalable AI solutions that align with\u00a0real business\u00a0objectives.\n\nOur work focuses\u00a0on:-\n<ul>\n \t<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"6\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\">AI strategy and architecture<\/li>\n \t<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"6\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"2\" data-aria-level=\"1\">Custom AI application development<\/li>\n \t<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"6\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"3\" data-aria-level=\"1\">Data readiness and integration<\/li>\n \t<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"6\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"4\" data-aria-level=\"1\">Enterprise AI implementation<\/li>\n<\/ul>\n<h2>AI Adoption Insights Infographic<\/h2>\nBelow is a visual summary of the insights gathered from our survey at the\u00a0AI Impact Summit 2026.\n\n<img decoding=\"async\" src=\"https:\/\/sapidblue.com\/blog\/wp-content\/uploads\/2026\/03\/LinkedIn-3.png\" alt=\"\" \/>\n\n<!-- \/wp:paragraph -->\n\n<!-- wp:heading {\"level\":3} -->\n\n<!-- \/wp:heading -->","protected":false},"excerpt":{"rendered":"<p>Artificial Intelligence is no longer a distant innovation. Across industries, organizations are actively exploring how AI can improve operations, enable better decision-making, and unlock new business opportunities. To understand how organizations are progressing on this journey, we conducted\u00a0a short survey\u00a0with booth visitors at the\u00a0AI Impact Summit 2026. The survey captured perspectives from\u00a050 industry professionals, including [&hellip;]<\/p>\n","protected":false},"author":10,"featured_media":6431,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[21],"tags":[],"class_list":["post-6313","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai","entry","has-media"],"_links":{"self":[{"href":"https:\/\/sapidblue.com\/blog\/wp-json\/wp\/v2\/posts\/6313","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sapidblue.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/sapidblue.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/sapidblue.com\/blog\/wp-json\/wp\/v2\/users\/10"}],"replies":[{"embeddable":true,"href":"https:\/\/sapidblue.com\/blog\/wp-json\/wp\/v2\/comments?post=6313"}],"version-history":[{"count":103,"href":"https:\/\/sapidblue.com\/blog\/wp-json\/wp\/v2\/posts\/6313\/revisions"}],"predecessor-version":[{"id":7562,"href":"https:\/\/sapidblue.com\/blog\/wp-json\/wp\/v2\/posts\/6313\/revisions\/7562"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/sapidblue.com\/blog\/wp-json\/wp\/v2\/media\/6431"}],"wp:attachment":[{"href":"https:\/\/sapidblue.com\/blog\/wp-json\/wp\/v2\/media?parent=6313"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/sapidblue.com\/blog\/wp-json\/wp\/v2\/categories?post=6313"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/sapidblue.com\/blog\/wp-json\/wp\/v2\/tags?post=6313"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}