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ROI in AI

By 2025, artificial intelligence has transitioned from experimental technology to a strategic necessity, with 78% of organisations adopting AI and global corporate investment reaching $252.3 billion in 2024.

Despite this surge, a significant "GenAI divide" exists where only a small minority of firms successfully scale initiatives to generate substantial financial impact, whilst 70-85% of projects fail due to obstacles such as poor data quality and inadequate governance.

Organisations that do manage to scale are realising an average return of $3.70 for every dollar invested, with productivity gains particularly notable in software development and customer service sectors.

However, the workforce landscape is shifting drastically; while AI boosts individual productivity, 41% of employers anticipate reducing headcounts within five years, creating a bifurcated labour market that favours high-skilled workers.

Looking ahead, the focus is shifting towards "Agentic AI" for autonomous workflows, though this introduces greater complexity regarding integration and safety compared to standard generative models.

Successful implementation now requires a move beyond isolated pilots to holistic transformation, necessitating robust data foundations and clear executive ownership to overcome the "pilot purgatory" that traps many enterprises.

ROI in AI

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Podcast Breakdown

1

Relentless Hype Meets Adoption Reality

The gap between AI marketing promises and actual implementation results.

2

High Spending Versus Project Failure

Organizations investing heavily in AI while many projects fail to deliver expected returns.

3

Understanding The Skewed ROI Math

Why traditional ROI calculations don't capture the full picture of AI investments.

4

Total Cost Of Ownership Shock

Hidden costs beyond initial implementation that impact AI project viability.

5

Augmentation Over Replacement Strategy Shift

Moving from AI replacing workers to AI enhancing human capabilities and decision-making.