AI inference and reasoning capabilities disrupt traditional, linear flowcharts and employees must shift their approach to orchestrating the work of AI agents, Ben Beath says.
governance
Procurement leaders expect AI to drive innovation and accelerate core processes, but first they need to reinvent their operations and get their people on board.
Tech, business, and finance pros will each have their own major areas of economic focus as they migrate AI apps from pilot to production to scale.
Leaders are banking on fewer transaction errors and stronger compliance from their AI investments. But there’s an architectural mismatch between ambitions and operating models.
Microsoft AI stack is a stark contrast to gaps exposed by OpenAI security incidents. It provides governed agent identities, evaluation and safety red teaming, and limits on agent blast radius.
Copilot Studio feature called Hooks adds certainty to the launch of workflows by agents, rather than rely on agents to make a judgment call.
As AI takes hold in production use cases, we need to ask a financial question: what happens to the bill if adoption expands broadly?
As it takes on work ranging from coding to running productivity apps to combining existing AI experiences, Copilot emerges as the driver of an expanding range of business activities.
Top users redesign workflows to give agents stable processes and provide persistent context so they can perform recurring work without repeated explanations.
Claude for Financial Advisors adds to an expanding set of industry-optimized AI software that automates and streamlines core functions performed by financial pros.
Tom Gerdes explains why cross-functional data governance is critical for uncovering hidden data risks and establishing the processes needed to address them as AI expands access to enterprise information.
CJ Combs explains how cross-functional data governance can help enterprises uncover hidden data risks, establish accountability, and build processes to remediate them.
Experts including forward-deployed engineers (FDEs) are deemed key factor in accelerating outcomes, reducing risk, and ensuring operational impact of AI.
Customers increasingly wonder whether communications, statistics, and research were reviewed by people, driving the need for published AI policies to build trust.
‘Project HydraFusion’ evaluates each request and chooses the least complex workflow required, using additional model calls only when it anticipates a better result.
Product provides budgets, guardrails, and lock triggers to actions taken by AI agents. Can organizations define clear limits and policies to make use of those controls?
New tools aimed at enforcing cost discipline include an AI pricing calculator, detection of spending anomalies, and spending caps for individual AI projects.
New features enhance positioning of Teams as a platform to support humans, agents working together to accelerate GitHub-powered dev projects.
Gmail, Calendar, and Drive users can now access data and perform tasks directly from their Claude conversations, accelerating integration of AI tools and productivity tools.
Microsoft’s Copilot Acceleration Team provides a rich, open-source repository of pre-written skills for specific tasks. Users need to exercise caution because they’re not supported product features.