Articles on AI Strategy

Everyone has an AI platform and a polished demo. Here are the questions that separate real AI solutions from sales theater in 30 minutes.

AI tools help junior employees produce senior-looking work. The gap between looking capable and being capable is where organizations get hurt.

AI coding tools feel like they're working, but the data says otherwise. The best engineers aren't coding faster — they're asking better questions.

95% of enterprise AI tools never reach production. A polished sales demo doesn't mean competent delivery — here's how to evaluate AI vendors.

Build, buy, or wait? Most AI projects fail because teams pick technology before understanding the problem. Here's a framework for getting it right.

Companies poured $109B into AI in 2024, yet productivity stats haven't moved. Is this an infrastructure build-out or a sophisticated bubble?

Companies rush to implement AI without documenting the institutional wisdom that makes them competitive. The result: faster operations but weaker differentiation.

A CTO couldn't tell his board what AI tools the company was using. Most organizations can't answer basic questions about their AI spending either.

$2.3M spent, and nobody used the platform. Three strategic questions — skipped by most leaders — separate AI success from expensive experimentation.

AI is becoming a commodity. Your competitive advantage from 'having AI' expires fast. The real question: what do you do when everyone has the same tools?

Renaming your analytics dashboard to 'AI Insights Platform' isn't strategy — it's AI washing. Here's why that creates compounding strategic debt.

An AI architect posted 'Naive RAG sucks' with no explanation. When experts stop explaining trade-offs, leaders make million-dollar decisions on opinions.

Stop planning the AI revolution. Companies winning with AI focus on steady improvements to basic operations, not flashy transformation projects.

Most companies burn millions on AI that solves the wrong problems. The difference between AI strategy and the AI graveyard is focus.

I watched a company burn $1.3M on AI while their data lived in 12 disconnected systems. Your AI project is doomed without a data foundation.

31% of employees actively resist their company's AI strategy — and the top reason isn't tech concerns, it's feeling devalued. Here's how to fix it.

Middle managers are caught between AI strategy and frontline execution. Here's how their roles are changing and what skills they need now.

Companies racing to implement AI are making more decisions, but worse ones. Speed without direction just means reaching the wrong destination faster.

I built a SmugMug replacement in five hours with AI tools. When competitors can replicate your product that fast, your value proposition needs rethinking.

Start with business problems, not AI solutions. Here's how to separate real AI opportunities from expensive distractions — and when to wait.

McKinsey's latest AI survey shows what separates experimentation from real value: workflow redesign, CEO oversight, and meaningful KPIs.

AI moves fast, but strategic principles don't change. Here's how to apply timeless thinking to navigate the compressed AI hype cycle.

Most companies are stuck between AI ambition and execution. A five-step framework to move from boardroom conversations to measurable business value.

The orgs winning with AI aren't the ones with the biggest budgets — they're the ones connecting AI directly to business outcomes. Build your flywheel.

AI Agents are part real advancement, part marketing rebrand. Here's how to cut through the hype and find where they actually deliver value.

I use AI daily — not to replace my thinking, but to multiply my output. Here's how I leverage AI for coding, research, and content.

Anthropic analyzed 4M+ AI conversations to reveal where AI actually gets used. The data shows augmentation wins over automation, 57% to 43%.

Everyone's impressed by what AI can produce. But flashy outputs aren't business outcomes — and confusing the two is an expensive trap.

AI moves fast. Here's a practical approach for business leaders to stay current with what matters without drowning in every announcement.

AI can generate answers, but subject matter experts validate them. In the AI era, deep domain knowledge is more valuable than ever — not less.

AI's real value comes from rigorous verification, not blind trust. Critical thinking and validation separate useful AI from expensive mistakes.

Multi-agent AI systems are moving beyond chatbots. Here's how orchestrating AI agents can transform operations — and why starting small wins.

A practical guide to AI for executives: understand machine learning, NLP, and computer vision — then learn how to implement AI strategically.

Viewing AI as just a cost-cutting tool is short-sighted. Its real power is freeing people to focus on creativity, strategy, and innovation.

AI leadership isn't about becoming a tech expert — it's about adaptability, vision, and ethical responsibility. A practical guide for CxOs.

My grandfather fed hogs with leftovers nobody wanted. In business, your messy, raw data is the same kind of 'slop' — and AI can turn it into insight.

AI has vast knowledge but zero wisdom. Here's why that gap matters and why human judgment, context, and experience remain irreplaceable.

AI investment isn't optional — it's a strategic necessity. Here's how to pick the right AI projects, align them with your goals, and manage risk.

As we delegate more decisions and emotional labor to AI, we risk losing compassion, empathy, and connection. AI should be a partner, not a replacement.

AI is only as good as your data. Without strong data habits — governance, quality, and ownership — even the best AI systems will fail.

Using ChatGPT for emails isn't 'doing AI.' Real implementation means building models, integrating systems, and learning from failure. Here's how.

Five areas where AI transforms operations and five challenges you must navigate. A practical guide for C-suite leaders implementing AI.

LLMs aren't creative — they're enhancers. Like Lightroom for photography, AI tools help you do what you do better, not replace the work itself.

LLMs can transform customer service, content, and research — but they hallucinate, lack reasoning, and need guardrails. A balanced guide for leaders.

AI ethics isn't optional — it's foundational. Five opportunities and five challenges for building a responsible AI-first culture in your organization.

There's a big gap between implementing AI and building an AI-first culture. Five strategies and five challenges for making AI part of your DNA.

AI isn't just for enterprises. SMEs can leverage affordable AI tools for customer service, marketing, and sales — here's how to start smart.

The 'brochure costs' of AI are only 30% of the real investment. Data prep, compliance, change management, and opportunity costs make up the other 70%.

Data scientists, engineers, and business teams in separate corners kill AI projects. Here's how to build cross-functional teams that deliver.

People are blindly trusting AI outputs without questioning them. Here's how to maintain critical thinking while leveraging AI effectively.

67% of orgs are doubling GenAI investment, but 68% have moved less than 30% of experiments to production. Here's what's blocking scale.

AI is democratizing expertise and changing how companies compete. Here's how to rethink strategy when rare knowledge becomes widely accessible.

The biggest hurdle in AI transformation isn't the technology — it's people. Communication, skills development, and culture determine adoption or failure.

The real AI leadership challenge isn't technical — it's balancing automation with human connection. Here's how effective leaders are adapting.

While everyone chases ChatGPT, the real AI revolution is about augmenting human thinking — not automating tasks. Most organizations are missing it.