A plethora of reports highlight the prevalence and dangers of AI hallucinations and other forms of inaccuracies resulting from AI applications. These errors can be traced to many different root causes, but the solutions boil down to a few methods: restrict the content to a carefully defined and structured set of validated information, protect the application through governance and monitoring, and evaluate the output to provide continuous improvement.
Judith Lamont //
14 Sep 2026
Organizations are moving AI from isolated tasks into everyday operations. A tool that started out drafting emails or summarizing documents may soon be asked to search internal files, retrieve customer information, prepare transactions, route requests, or update records.
Colin Levy //
18 Sep 2026
It should come as no surprise that AI has already infiltrated many parts of daily life. After all, AI has been around for decades. Still, some people are amazed to discover that things they take for granted, such as spellcheck, autocorrect, real-time traffic maps, spam filters, ride-hailing apps, and personalized music recommendations, are AI-enabled. The more that AI-enabled tools become embedded in daily routines, the less they seem to be advanced technology and more just a normal part of life. It's no longer magic, it's normal.
Marydee Ojala //
25 Sep 2026
The intricacies of the time-honored question of whether to build or buy take on new dimensions when it comes to enterprise AI. Organizations must not only account for traditional considerations like cost, time-to-market, and proof of concepts but also for those that are unique to advanced machine learning and language model deployments.
Jelani Harper //
08 Jun 2026