Tines Study Highlights IT's Role in Scaling AI Responsibly
A recent study by Forrester Consulting, commissioned by Tines, highlights the significant challenges enterprises face in scaling AI, with security and governance concerns being the most cited barriers. The study surveyed 417 IT leaders from North America and Europe, revealing that 38% of respondents identified security issues as a primary obstacle, followed by budget constraints (35%) and unclear ROI (34%) according to the study.
The research underscores the pivotal role of IT leaders in orchestrating AI strategies to ensure secure and scalable implementations. IT departments are seen as essential in embedding AI into existing workflows without disruption, with 38% of respondents advocating for IT to lead AI orchestration. The study also notes that IT's involvement can transform it from a reactive support function to a strategic driver of business transformation.
Key priorities for IT teams over the next year include ensuring AI solutions meet privacy and governance requirements (54%), enhancing employee experience through privacy-conscious IT capabilities (44%), and reducing IT costs without compromising compliance (42%). The study emphasizes that by prioritizing orchestration, IT can help organizations scale AI responsibly and achieve measurable business outcomes.
We hope you enjoyed this article
Consider subscribing to one of our newsletters like Enterprise AI Brief or Daily AI Brief.
Also, consider following us on social media:
More from Enterprise
Oct 16 BOC Group Adds AI Assistant to ADOIT 21 Oct 16 Huawei Brings Upgraded Stellar Network Solution to Europe Oct 16 Element to Manage Waymo's Toronto Fleet for 2028 Launch Oct 16 CTM and Huawei Plan AI Network Security Upgrades in Macao Oct 16 Huawei and 14 partners form Global AI CITY allianceEnterprise AI Brief
Weekly report on AI business applications, enterprise software releases, automation tools, and industry implementations.
Whitepaper
Tensordyne Napier: What If One Rack Could Do the Work of Nine?
Tensordyne
This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.
Read moreYou may also like
Small Banks Lead Peers in AI Readiness but Struggle to Scale
IFS survey finds frontline teams lead industrial AI adoption
Center for Talent Innovation Warns AI Work Redesign Can Erode Skills
IBM survey finds 80% of EMEA executives escalated AI incidents to senior leaders
IBM Study Finds Gap on Critical Thinking Skills for AI
Daily AI Brief: the AI news that matters, in your inbox.