Is Your Business Model Helping or Hindering AI Digital Transformation?

82% of organisations globally have already invested in Artificial Intelligence (AI) and another 33% are doubling their investment in the coming year, according to design software company Orgvue. And Goldman Sachs Research estimates global AI investment could reach $200 billion by 2025. In short, AI transformation is now firmly on the C-Suite agenda.

But there’s a problem. Successful digital transformations are notoriously hard to accomplish. A McKinsey Global Survey found that only 20% of companies achieved more than three-quarters of the revenue gains anticipated, and only 17% achieved more than three-quarters of the cost savings they’d hoped for. The problem isn’t the tech, it’s the business model itself.    

With that in mind, what lessons can you learn from failed digital transformation initiatives and how can you set up your business to make the most of the AI revolution?   

Out with the old: The traditional business model   

Traditional business models aren’t set up to deliver sweeping, enterprise-wide technological change. They spare little room for company-wide innovations that cater to rapidly changing customer demand.   

So, what are the main issues holding businesses back?   

1. Lack of agility   

Hierarchical structures in traditional models delay decision-making and impede the rapid iteration needed for AI-driven innovation. Accenture’s 2023 research shows that businesses that adopt an agile mindset, especially in workforce strategy, see a three-fold increase in productivity​.   

2. Siloed data systems   

In traditional business models, data often exists in isolated systems, creating silos that hinder effective data usage for decision-making. According to a study by Gartner, 85% of data science projects fail due to poor data quality and siloed systems. This directly challenges businesses relying on legacy infrastructures to support AI transformations.   

3. Resistance to change   

Traditional models are often rooted in well-established routines and practices. A Thomson Reuters 2023 C-Suite survey found that many executives identified employee resistance and outdated leadership practices as top barriers to successful transformation.   

Your AI-transformation-ready checklist   

Understand where your business model weaknesses are with our AI-transformation-ready checklist. If you answer ‘yes’ to most questions, use this article to help rethink your digital strategy:   

1. Does your organisation have data siloed in separate systems?   
2. Are you still relying on legacy infrastructure?   
3. Is there widespread resistance to adopting new technologies within your business?   
4. Does your organisation lack a clear, company-wide strategy for AI?   
5. Is your business model reliant on hierarchical, slow decision-making processes?   
6. Do your employees lack AI and data expertise?  
7. Are digital transformation efforts focused more on internal processes than customer needs?   
8. Is your organisation reactive to technological trends rather than proactively pursuing innovation?   

In with the new: The transformational business model   

For AI transformation to succeed across the entire business it requires change management at a fundamental level.    

Companies like Amazon, Google, Airbnb, Netflix, and Expedia have all evolved their business models from traditional to tech-integrated — driving innovation and creating customer experiences focused on convenience, value and efficiency.   

So, how can you evolve your operation to succeed like Amazon, Netflix, and Google?   

1. Put customers front and centre   

“Every digital transformation is going to begin and end with the customer, and I can see that in the minds of every CEO I talk to.” — Marc Benioff, Chairman and CEO, Salesforce.   

To avoid overpromising and under-delivering it’s important to set clear, realistic goals for what your AI transformation will deliver to customers. Think about the job you’re helping them do and frame your initiatives around that rather than the products you deliver. Align changes with customer demands and roll out updates in phases, ensuring your team is trained and ready.  

How can you achieve that?  

Use your data to help guide your decision making. Understand which platforms your customers use and what they engage with. Complement this with UX research to ensure any changes you implement align with user preferences for a seamless customer experience.  

2. Deploy modern systems   

“Firms that want successful AI digital transformations must go deeper by ensuring that they have modern systems throughout their technology estate and equipping their people with the skills to operate them,” explains Ruben Schaubroeck, Senior Partner at McKinsey.  

Modernising your tech stack is a huge task, and poor planning can lead to failure — like apps crashing or features breaking. The result? Damaged reputation and lost customer trust. Plan wisely to avoid setbacks.  

What should you do?   

Audit your existing tech stack to replace or remove outdated tools, consolidate your data into one place to get a 360 view of your customers, and assess your cloud requirements — do you need public, private, or hybrid? Following these three steps will help you deploy modern systems seamlessly.  

3. Equip employees with the right skills   

“Generative AI is not only here to stay, but it is the fastest evolving technology I have ever seen. Organisations and individuals must take steps now to hone their knowledge in this area.” — Maureen Lonergan, vice president of AWS Training and Certification.   

As well as ensuring you’ve the right infrastructure in place, it’s important to remember that AI digital transformation reshapes how employees work. Poor communication and talent gaps are top reasons for failure. Keep teams educated, informed, and empowered to succeed.   

How can you do that?   

When implementing changes, clearly communicate what’s being done, why it’s necessary, and how it’ll impact employees. Upskilling is important but so is recruiting skilled workers who can operate new technologies. 

Next steps: An AI digital transformation future   

The path to a successful AI transformation requires more than investment — it demands a shift in mindset, technology, and talent. AI is revolutionising how businesses operate, and leaders must create a clear roadmap for customer needs, innovative infrastructure, and a skilled workforce. Now is the time to act, plan, and execute.