Enterprise AI strategy fails most often not because the technology is wrong, but because the organisational conditions are wrong. Companies buy tools before they have defined problems, run pilots before they have governance, and measure activity instead of outcomes. The result is a portfolio of subscriptions that nobody fully uses and a leadership team that…
Agentic AI in customer experience refers to AI systems that can take autonomous, multi-step actions on behalf of a customer or business, without waiting for a human to approve each move. Unlike a chatbot that answers a question, an agentic system can detect a delivery problem, initiate a refund, send a follow-up message, and flag…
AI’s impact on sales and marketing in 2023 was real, uneven, and frequently misread. The tools improved faster than most teams could absorb them, adoption outpaced strategy, and a lot of the noise obscured what was genuinely useful from what was just new. The clearest shift was not in capability, it was in accessibility: AI…
A solid AI adoption strategy is the difference between a team that uses AI to do better work and a team that has a ChatGPT tab open and nothing to show for it. Most marketing teams sit closer to the second camp than they would admit, not because the tools are bad, but because adoption…
Omnichannel retail marketing is the practice of connecting every customer touchpoint, in-store, online, mobile, email, social, into a single coherent experience where each channel reinforces the others. The goal is simple: customers should feel like they’re dealing with one brand, not a collection of disconnected departments. In practice, most retailers are nowhere near that. The…
AI search marketing is the practice of optimising how your brand appears across AI-powered search experiences, including generative answers in Google, Bing Copilot, and standalone tools like ChatGPT and Perplexity. It sits alongside traditional SEO but operates on different logic: instead of ranking a page, you are influencing whether an AI system surfaces your brand,…
AI strategy development is the process of deciding, at an organisational level, which AI capabilities you will build, buy, or ignore, and why. It is not a technology project. It is a business decision with a technology dimension, and the two are easy to confuse when vendors are doing the talking. Most marketing teams are…
Artificial intelligence and business strategy intersect most productively when organisations stop asking “what can AI do?” and start asking “what business problem are we actually trying to solve?” The technology is capable. The strategy, in most companies, is not keeping pace with it. That gap is where most AI investments quietly underperform. Not because the…
McKinsey’s superagency concept describes a future where AI doesn’t just assist workers but actively amplifies what they can do, shifting organisations from AI-augmented teams to AI-native ones. The implementation challenge isn’t technical. It’s structural, cultural, and commercial, and most agency leaders are not ready for it. The McKinsey Global Institute’s research on workplace AI paints…
AI strategy consulting is a service that helps organisations assess where artificial intelligence can create genuine commercial value, identify the gaps in capability and process that would prevent it, and build a roadmap for implementation that holds up when it meets real operational constraints. Done well, it is one of the more useful engagements a…
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