AI Strategy
Strategic guidance on implementing AI capabilities at organisational scale. Our articles address capability assessment, adoption roadmaps, integration challenges, and how to build competitive advantage through AI. Practical frameworks informed by hands-on implementation experience across industries.
36 articles
Best Consulting Firms for Defining Your AI Strategy in 2026: An Honest Buyer's Guide
This guide argues that choosing the right AI strategy consultant depends on matching your company's specific needs, size, and budget to the appropriate type of firm (whether global consultancies for enterprise credibility, specialist boutiques for technical depth, or independent consultants for focused expertise) rather than simply picking the most famous name.
The key metrics to measure the ROI of your LLM deployments
Most organisations measure LLM success using traditional software metrics whilst sitting on transformational cognitive infrastructure they barely understand how to evaluate properly.
EU AI Act Explained: Compliance Requirements and Business Impact
The EU AI Act's extraterritorial reach and risk-based classification system will reshape global AI development by creating competitive advantages for organisations that build regulatory compliance into their systems from conception rather than retrofitting it later.
Why Most AI Projects Fail Without Expert AI Consulting
Most organisations fail at AI because they mistake building models for building systems, burning millions on architectural decisions that doom projects from the start whilst ignoring the expertise gap that separates proof-of-concepts from production reality.
Building a Secure LLMOps Pipeline: From Development to Production
Most organisations treat LLM security like traditional DevOps while ignoring novel attack vectors through model weights, training data, and prompt injection that conventional tools cannot detect.
Why tokenization matters: CharGPT vs ChadGPT
GPT-4 struggles to count letters in "CharGPT" versus "ChatGPT" because tokenisation (the process of breaking text into processable units) fundamentally shapes what AI models can perceive, revealing why some companies' AI implementations fail at the architectural level rather than the reasoning level.
Thin wrapper or true AI? Technical due diligence for AI investments
Despite widespread AI claims in company pitch decks, 95% of generative AI pilots are failing, creating a massive gap between marketing promises and reality that requires rigorous technical due diligence to distinguish genuine AI capabilities from superficial implementations.
Best AI consultancies for 2026: navigating the agentic era
AI consulting in 2026 shifts from strategy to implementation as enterprises demand partners who can actually build and deploy working AI systems, not just create PowerPoint decks.
The business applications of reinforcement learning: why most enterprises are leaving billions on the table
Most companies are building static AI calculators when they could create adaptive systems that continuously optimise performance through environmental interaction—missing billions in potential value through reinforcement learning applications.
Finding a trusted AI consulting partner: beyond the marketing veneer
Most AI consultancies are selling yesterday's chatbots whilst genuine expertise lies in architecting sophisticated systems that exploit technical potential others cannot even perceive.
The leader's guide to building AI aptitude in your organisation
Most organisations treat AI implementation like building rudimentary websites in 1995: functional but missing the architectural sophistication needed to exploit AI's genuine competitive potential beyond basic automation.
AI-enhanced scenario planning: techniques for modern boardrooms
Modern boardrooms are squandering AI's potential in scenario planning by digitizing outdated methods rather than implementing sophisticated systems that explore true possibility spaces through causal inference, complex adaptive modeling, and counterfactual testing.
Cost-effective LLM implementation: when to fine-tune and when to prompt
Most companies are burning money on LLM implementations by defaulting to expensive fine-tuning when sophisticated prompting could achieve comparable results at a fraction of the cost and complexity.
AI governance: what business leaders need to know
Most organisations are building AI compliance theatre whilst competitors build capability fortresses, treating governance as bureaucratic overhead rather than the competitive advantage that enables sustainable AI deployment.
From guidelines to guardrails: operationalising AI ethics in product development
AI ethics must shift from performative checkbox exercises to embedded technical guardrails that transform ethical principles into operational constraints throughout the entire development lifecycle.
Hiring a fractional head of AI to complement your existing technical team
A fractional Head of AI bridges the critical gap between technical expertise and strategic AI leadership, enabling organisations to unlock their AI potential without the overhead of a full-time executive.
Self-improving systems: the AI architecture pattern everyone talks about, nobody builds
Despite the hype, truly self-improving AI systems remain theoretical due to fundamental technical and organizational barriers, with today's "self-improving" implementations being merely constrained optimization within predetermined parameters.
Parameter-efficient fine-tuning: what business leaders need to know
Parameter-efficient fine-tuning revolutionises AI model customisation by enabling comparable performance with just a fraction of the computational resources, offering businesses a strategic advantage over competitors using outdated, expensive full-model approaches.
The curse of dimensionality: when more data becomes your enemy
The curse of dimensionality paradoxically undermines AI performance as data dimensions increase, creating mathematical conditions where distance metrics collapse and models fit noise rather than signal.
Richard Sutton's bitter lesson explains why your AI solution feels shallow
Sutton's bitter lesson reveals that most AI implementations feel shallow because they prioritize domain expertise over computational scale, leaving roughly 80% of potential untapped.
Top AI consulting companies for 2025: the rise of boutique technical excellence
In 2025, boutique AI consulting firms are outpacing traditional giants by offering tailored, innovative solutions that meet specific client needs, reshaping the consulting landscape.
Beyond the hype: creating measurable ROI with LLM implementations
Despite their transformative potential, Large Language Models (LLMs) necessitate robust evaluation and strategic implementation to ensure they deliver real value rather than becoming a costly gamble.
The Non-Executive Director's guide to assessing AI system performance
The guide equips Non-Executive Directors with essential frameworks and insights to effectively assess AI system performance, ensuring alignment with corporate objectives and ethical standards.
Creating custom benchmarks that align with business objectives
Custom benchmarks, tailored to specific business objectives, are essential for driving meaningful performance insights and strategic success, far outperforming generic metrics.
The fractional CTO's guide to building AI teams that deliver
The Fractional CTO's Guide highlights the crucial role of fractional CTOs in building high-performing AI teams that align with business objectives while fostering innovation and ethical practices.
The strategic value of a Non-Executive Director with AI expertise
The inclusion of Non-Executive Directors with AI expertise is essential for organisations to effectively navigate the complexities of modern business strategy and ethical considerations in an increasingly AI-driven landscape.
An executive’s guide to AI agents
AI agents are transformative software entities that enhance operational efficiency and decision-making in businesses by autonomously performing tasks and leveraging advanced technologies like generative AI.
Common technical challenges fractional CTOs solve for startups
Fractional CTOs provide expert technical leadership to startups, addressing critical challenges like technical debt, scaling infrastructure, security, and cloud cost optimisation without the need for a full-time hire.
Unlocking business potential with AI agents
AI agents are intelligent systems that autonomously handle tasks, enhancing efficiency and reducing costs.
Building your AI-first company
The rise of AI-first lean startups: rethinking organisational structure in the genAI era
Should I build my own large language model (LLM)?
Organizations considering building their own large language models (LLMs) should weigh the benefits of control and specialisation against challenges like high computational needs and expertise requirements.
Who are the best AI consulting firms in 2024?
When selecting an AI consulting partner, the right fit will depend on your organisation's unique needs, budget, and desire for a hands-on collaborative engagement.
Delivery excellence through multi-disciplinarity and diverse teams
Unlocking the potential of AI through diverse teams: why it is crucial to employ a multidisciplinary team
What is multi-modal AI?
Multi-modal AI represents the evolution from single-stream processing to systems that integrate multiple information types (text, images, audio) simultaneously—mimicking human cognition and unlocking transformative capabilities most organisations fail to fully exploit.
Quantifying the benefits and risks of an AI deployment
How we at Agathon quantify the benefits and risks of any project we embark upon
Responsible and ethical AI — why does it matter?
Responsible AI is all the rage, but why should one care?