Overcoming AI barriers

For all the novelty of AI, the barriers are frustratingly familiar.
Read the next chapter Contact an AI expert
Light blue background with shades of darker blue tones

Meet the new blocks (same as the old blocks)

Over half the people we asked described each of these factors as a barrier to AI adoption in 2024:

•    IT and cloud systems that were underpowered or fragmented
•    Data privacy, security, management or alignment concerns
•    Lack of workforce skills and attitudes

But only about a third of those same people predicted these same issues will still be barriers in 2026.

Big if true. But these problems have long plagued companies. How to overcome them now?

Strengthen tech foundations… but think beyond IT

The proportion of companies with IT systems ready for AI is projected to almost double between 2024 and 2026—from 26% to 45%.

In other words, over half of respondents still expect to be less than completely ready. And even if you’ve cleared this first hurdle, keep in mind that technology investment alone won’t solve a readiness problem.

Discover expertly curated insights and news on AI, cloud and more in the weekly Think Newsletter.

Subscribe today

Put your money where your strategy is

AI readiness is multifactorial, so your preparations should be too. Our surveys showed these top priorities for AI investment:

Investment focus 2024
-    Enhancing internal skillsets to deploy and work with AI
-    Ensuring data readiness
-    Enhancing reliability of AI results
-    Identifying the best suite of enterprise AI tools
-    Ensuring AI processes are as good as or better than manual

Investment focus 2026
-    Deploying AI enterprise-wide
-    Expanding AI use cases
-    Ensuring AI processes are as good as or better than manual
-    Enhancing AI reliability
-    Giving more users access to AI

R-O-why?

About two-thirds of our respondents across functions and levels of readiness report that proving ROI is not a top priority by 2026. Instead, they’re focused on AI adoption and developing use cases.
 
This makes sense. Despite a shortage of required skills, AI adoption is the single most cited strategic priority for companies—and strategic goals demand action now to pilot AI and experiment with solutions.
 
In this pilot phase, ROI may be hard to quantify. But AI leaders think it’s a risk worth taking. If you fall into the trap of seeing AI as a cost center, you may find it hard to catch up to competitors who take a longer view.

Chapters

AI Readiness - Chapter 1 representation with a white 1 and different shades of blue and purple in the background
Thriving through AI disruption
AI Readiness - Chapter 3 representation with a white 3 and green cubes in a dark blue background
Improving AI readiness now
Take the next step

Visit Think to explore the latest tech news, insights and education. Or book an AI discovery session with an IBM Consulting expert.

 

 

 Visit Think Contact an AI expert
Footnotes

Unless otherwise noted, statistics and quotations are drawn from original IBM research: 98 interviews and 1204 survey respondents in the US, Canada, UK, France, Germany, Italy, China, India, Japan and Australia, conducted March-June 2024. Respondents’ roles include key decision-makers with influence regarding the evaluation or selection of AI services or solutions. Primarily from businesses with 1,000+ employees (n=1,082), with some from mid-market (500–999 employees, n=122). Cross-industry mix focused on finance and banking, manufacturing, retail, energy and utilities, public, and telecommunications.

AI at Wharton, Growing up: Navigating Gen AI’s Early Years (Oct 2024)