AI Strategy
580 articles
Strategy work is where most AI programs are won or lost, long before a model gets picked. This is the planning layer: how to sequence a first year, which problems justify custom work, what to centralize versus leave to teams, how to budget when pricing shifts every quarter, and how to tell a real result from a demo. Aimed at operators at $5M+ companies who have to defend the spend.
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Should You Hire AI Talent or Build AI Capability In-House?
Hiring AI talent: 6–9 months, high turnover risk. Building in-house: 12–18 months to compound. Year-one cost and risk breakdown for $5M+ companies — and the hybrid path most end up taking. year-one costs, risk, and the hybrid path most $5M+ companies take
Generative AI and Copyright: What Businesses Need to Know
The key copyright considerations for businesses using generative AI to create content, code, and images, and practical risk management approaches.
Generative AI Capabilities: What It Can and Cannot Do Today
A practical assessment of generative AI capabilities for business teams: where it excels, where it struggles, and what this means for which workflows to automate first.
Generative AI for Business: The Complete Guide for 2026
The complete guide to generative AI for business: definition, capabilities, use cases, deployment, governance, and risk management.
Generative AI for Business: How to Use Gen AI to Drive Revenue
The complete guide to generative AI for business: what it is, how it works, the highest-value use cases, how to deploy it, and how to govern it responsibly.
Generative AI for Code Generation and Software Development
How generative AI accelerates software development: code generation, testing, documentation, and code review, and what development teams need to know to use it well.
Generative AI for Content Creation and Marketing
How marketing teams use generative AI for content creation, campaign development, SEO, and audience engagement, with practical workflows and quality controls.
The 5 Phases of AI Transformation for Business
The five phases of AI-driven business transformation, what happens in each phase, and what leaders need to do to move from one phase to the next.
GDPR and AI: Data Privacy Requirements for AI Systems
How GDPR applies to AI systems: training data, automated decision-making, data subject rights, and how businesses ensure their AI use complies with data protection law.
The Three AI Strategy Phases Mid-Market Companies Must Follow
Most companies run AI phases in the wrong order — and pay for it. Here's the three-phase model that runs from an AI Readiness Audit to AI-native operations.
The Three Phases of a Phos AI Labs Engagement
Every Phos AI Labs engagement moves through three phases: an AI Readiness Audit, an AI Foundation, and AI Implementation.
Enterprise AI Use Cases: Where Large Companies See the Best ROI
The enterprise AI use cases with the highest proven ROI, organized by business function, with specific examples of what enterprises are deploying in 2026.