AI Implementation Strategy KPIs: Why Success Starts Before the First Model
Your AI pilot did not fail. You just never defined what success looked like. Across industries, AI programs are getting built, funded, and deployed. But why do so many still stall somewhere between proof-of-concept and real business value? In most cases, the flaw lies not in the model’s accuracy,...
AI Isn’t a Product: Rethinking AI Product Strategy to Avoid the Internal Innovation Trap
Many enterprises confuse internal AI tools with strategic innovation. This article examines why AI initiatives must extend beyond internal efficiency to deliver real market impact. It explores product strategy, organisational change, and cultural integration—highlighting what it takes for AI to become a true driver of enterprise value....
From Use Case to Business Case: What an AI-First Strategy Really Requires
Many enterprises invest in AI pilots but struggle to scale them. This article explores what an AI-first strategy truly requires—from data readiness and operational ownership to measurable outcomes. Moving beyond isolated use cases, it outlines how organisations can embed AI into core workflows and deliver sustained business value....
The Illusion of AI: Why Most AI Implementations Are Skin-Deep and What That Reveals About The Strategy
Most AI projects fail not because of technology, but due to missing customer alignment and cultural readiness. This section explores how ignoring these two pillars undermines AI impact — and what leaders must do to fix it....
AI in Strategy Development: Transforming Decision-Making and Competitive Advantage
In an era defined by rapid technological change, AI in strategy development has emerged as a transformative force. Organizations across industries are leveraging artificial intelligence to process vast amounts of data, uncover hidden patterns, and enhance decision-making with predictive accuracy. The ability of AI to deliver real-time insights is...
Human Capital vs. Algorithmic Capital: Finding Harmony in Workplace Futures
As workplaces evolve, human creativity and AI efficiency are increasingly intertwined. This shift is reshaping collaboration, especially in co-working environments. Today, we explore how to balance human and algorithmic capital in the workplace....
Building Systems of Adaptation for Continuous Change – Beyond the AI Hype
hyper-connectivity, and AI are the constant backdrop of doing business. While digital transformation and artificial intelligence (AI) initiatives have become ubiquitous in boardrooms, many organizations remain trapped in cycles of reactive transformations. These episodic efforts may deliver short-term wins, but they fall short of equipping businesses for sustained relevance....
Data and Artificial Intelligence. The Fuel for the Fire
AI is only as good as the data it's fed. High-quality data is crucial for accurate and reliable AI models. Organizations must invest in data quality, availability, and security to unlock the full potential of AI....
The world of RPA needs Open Standards
As a technology develops, proliferates, matures along with demand, people start questioning its ability (or lack thereof) to deliver on promised improvements in innovation, new (or increased) revenue streams and cost savings and the like. Those three are the final outcomes in any case. And now, those questions are...
Is your RPA ROI getting eroded?
Though we all know that Process Automation, either simple RPA, or intelligent, can bring in 30-75% cost savings, we often see the ROI getting eroded. Why does that happen?...