AI can speed individual tasks while increasing downstream work for colleagues and the organization. Marketing leaders must set rules, measure workflows end-to-end, and prepare teams for shifting responsibilities.
Experimentation with AI is necessary, but leaders must set clear rules about when to use AI, required quality thresholds, and who is accountable for review.
Measure AI’s impact across the full content workflow — saving time for one person can create more total work if downstream fixes are required.
It's not enough to worry about AI slop reaching customers and burying editors, creative teams, and other experts in work they have to repair. There's a broader problem emerging inside organizations: AI can make an individual employee more productive while making the organization less efficient. If AI saves one employee 20 minutes but creates 30 minutes of work downstream for others, that's not a productivity win.
Those changes will take longer, and they understandably put employees on edge. Download The Guide Blog As AI Adoption Surges In B2B Marketing, Work Is Changing Ian Bruce 4 days ago Across B2B marketing, AI is no longer an emerging technology for experimentation or being tested on the sidelines. Experimentation without norms can push the cost of learning onto someone else.
In my new report, The State Of Content Creation And Optimization Solutions, 2026 (Forrester license required), 66% of marketing leaders say their organizations are still encouraging experimentation as they determine the right mix of AI capabilities for content and creative work. An editor spent 20 minutes correcting a draft. A customer received generic content that eroded confidence in your brand.
This year, I’ve been building an AI social media production pipeline to promote the 25+ shows on the Autistic Culture Podcast Network . It took me a week of effort, but I managed to program Claude Code to talk to NotebookLM, which now feeds our YouTube, Instagram, and TikTok pipeline, and a task that used to take me a
OpenAI disclosed that its researchers now supervise 3.14 agent-workdays for every 8-hour human workday. Rather than making programmers three times smarter, software development is turning into a 24-hour factory where inference behaves like heavy tooling capex running multiple shifts.
Before AI, I had 7 half-done projects sitting around. After AI, I have 87. Read that again. Faster building did not make me more finished. It made the pile bigger. Here’s the thing. AI lets you build automations and systems faster than you can comprehend them. You shovel a task at the model, it hands […]
Companies are racing to automate work without realizing they may also be automating away the systems that create expertise. That is the workforce challenge emerging beneath today’s AI conversation. Most debates focus on whether AI will replace jobs. But jobs are the wrong lens for this discussion. Work has always been
For decades, productivity in finance meant closing the books faster, reducing transaction costs and improving reporting. Artificial intelligence changes that equation, because it can do more than execute routine work. It can interpret variances, detect anomalies, generate forecasts, test scenarios and recommend actions
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