Artificial Intelligence (AI)
AI is speeding up work, but can your organisation keep up?
AI promises greater productivity, but hidden workloads, unchecked errors and growing risks are challenging that narrative. Erica Farmer explores why learning and compliance professionals must work together to rethink accountability, strengthen human oversight and equip employees with the confidence to challenge AI outputs before costly mistakes become big organisational failures. The one thing I hear myself saying to many people right now is, ‘there is no playbook for AI’. Typically, with new system and software deployments we rely on case…
Gen Z doesn’t want another training course
Gen Z is taking control of its professional development, but traditional training approaches risk holding young workers back. Trent Cotton explores why self-directed learning is reshaping expectations and how L&D teams can respond with personalised pathways, meaningful mentorship and opportunities that build on existing skills rather than starting from scratch. Think about an athlete who shows up to pre-season already in shape. They have done the work before competition time, studied the playbook and built their conditioning on their own…
Is it time to rethink how L&D measures AI success?
As AI transforms workplace productivity, traditional measures of learning success risk overlooking a growing skills gap. Dr Gleb Tsipursky explores why time to proficiency should become L&D’s defining AI metric, helping organisations assess independent judgement, preserve essential learning experiences and ensure employees develop expertise rather than increasing dependence on technology. The most urgent AI problem for L&D may be hiding inside a productivity win. When software drafts the routine email, summarises the case, prepares the first analysis and answers the…
Is AI making your organisation’s echo chamber louder?
AI promises smarter decisions, but can it also reinforce the assumptions organisations need to challenge? Jennifer L. Bryan explores why diverse perspectives, psychological safety and better questions matter when adopting AI, and how leaders can prevent powerful technology from turning familiar biases into increasingly convincing answers that nobody dares question. Artificial intelligence is changing how organisations gather information, analyse problems and make decisions. Yet as businesses rush to adopt increasingly powerful AI tools, there is a less obvious organisational risk…
The high-risk consequences of underprepared managers
Changing employment rules, rising workplace conflicts and easy access to AI-generated advice are putting managers under growing pressure. Nick McClelland argues that organisations must move beyond compliance-led training and give managers the confidence, judgement and practical conversation skills needed to resolve issues early, fairly and effectively before they escalate further. In 2026, my conversations have been dominated by one theme: manager and leader capability. Not as a general development aspiration, but as a pressing operational and people risk concern. The…
Beyond the prompt: What L&D teams should consider when implementing AI
L&D teams may be fluent in many AI tools, but true readiness requires more than adoption. Kristin Delgado explains why measuring human factors such as learning agility, critical thinking and reliance on AI can help learning leaders close confidence gaps, target support and guide organisations through digital transformation more effectively. When new challenges require an organisation to rethink existing ways of working, upskill staff, and redesign training, learning and development are promptly called to the rescue. As those responsible for…
Workers need to learn how to question AI, not just how to use it
As AI becomes commonplace at work, employees need more than technical know-how. Gray Mytton explains why workers must question outputs, spot errors and apply human judgement, while developing critical thinking, adaptability and curiosity to navigate changing tasks, emerging roles and increasingly AI-shaped workplaces with confidence and care in future work. Workers need to learn how to question and check AI-generated information rather than simply how to use AI tools, as new figures show AI use is becoming increasingly common across…
Why AI-Generated content is becoming harder for L&D teams to manage
As AI accelerates content production, Chris Van Wingerden stresses that L&D teams face a new bottleneck: managing the volume of learning content they can create. Drawing on dominKnow’s LCMS Report, he explores why content management, governance and human oversight are becoming essential to keeping AI-generated learning trustworthy, compliant and useful. For years, the learning industry has focused on one persistent challenge: creating enough content to keep pace with organisational change. Today, that challenge looks very different. AI has transformed the…
AI in Learning 2026: A day built for sensemaking, not just adoption
Slow down, question the hype and reclaim a voice in workplace AI decisions. Julie Drybrough explores why L&D and HR professionals need space to make sense of fast-moving technology, examine its practical and ethical implications, and shape how AI is adopted rather than simply implementing choices made elsewhere for them. How much AI information can any of us actually process before “keeping up” starts to feel like drowning? That was one of the questions that prompted Fiona McBride (Fiona McBride…
AI is changing work. Is L&D changing fast enough?
Dr Ravinder Tulsiani argues that generative AI demands more than basic tool training. L&D must map AI to real work, build judgement and validation skills, update competency frameworks and measure performance impact. The opportunity is to move beyond content delivery and redesign capability for an increasingly AI-enabled workplace at scale. Generative AI is reshaping how work happens. L&D professionals need to look at what exactly is changing about work and how we should we respond. A major Microsoft Research study…
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