AI and the C-suite

Dave McCann at IBM Consulting Europe shares the secret to C-suite success in leading the AI revolution 

 

2023 was the year that generative AI captivated consumers and businesses. Almost a third (29%) of enterprises have implemented the technology, and 43% are in the exploration phase of their AI journey.

 

2024 will be the year we move beyond the hype and focus on driving real value from the technology. For business leaders, the priority over the next twelve months and beyond will be identifying how AI can drive significant commercial results, whether that’s through cost and operational efficiencies or improved customer service. To make digital transformation a reality, and a success, investing in research and development will be top of the priority list for more than a third of organizations deploying or exploring AI.

 

The true value of AI  will be unlocked not by those who follow the trends but by those who create them. There are four strategies  business leaders should embrace to lead the AI revolution.  

  

1.     Create value from AI

There are three distinct modes of consumption of generative AI: the first is to buy software that has generative AI embedded in it, the second is to query third-party models through API calls, and the third is to create (and then query) your own foundation models leveraging public and private data. 

  

Today, most enterprises focus on the first two AI adoption patterns because they offer the most time and cost-efficient way to experiment and discover valuable use cases.  

 

However, enterprises must carefully consider the competitive advantage of leveraging their own data through their own foundational models. Any enterprise that wants to get the most out of AI should participate in the full value creation opportunity of foundation models rather than outsourcing their capacity, their strategy, and — most importantly — their data to third parties. 

 

A business that can create its own AI models is a business that controls its success.  Not only can they train, tune, and govern their AI tools to consistently get the most out of these evolving technologies — as value creators, they have real ownership over the protection, control, and development of their applications. 

 

Creating a foundation model may seem daunting, which is why having the right technology partners to guide and scale with is critical for success.

  

2.     Bet on community

The AI revolution will be propelled by the energy and ingenuity of the entire AI community.  By integrating the best open-source models, private models, and their own created models, businesses stand to make the most of that community. 

 

An open approach to AI is important from an ethical standpoint. An open ecosystem will not only promote competition, skilling, and security, it will also help ensure that the industry is shaped by diverse and inclusive voices. 

 

All workers should be included in a business’s AI journey so the technology becomes intrinsically linked within its culture and processes. A quarter of organizations are already training employees to collaborate and engage with AI and automation, and in 2024, more than a third of businesses (36%) will invest in reskilling or upskilling their workforce to accelerate that trend.  

 

3.     Ensure AI can run everywhere and run efficiently

AI is benefitting operations across organizations. IT professionals are at the forefront of AI usage and, as a collective, recognise the importance of being able to build and run AI projects wherever data resides. Encouragingly, 80% of IT professionals are confident their company has the tools in place to curate data from right across their enterprise. 

 

Businesses can optimize cost, performance, and latency by building open, hybrid cloud technologies. Innovation is making it easier for businesses to manage their most valuable data, and to train, tune, and deploy AI models seamlessly between public and private clouds. The future of these technologies rests on agile, cost, and energy-efficient options for businesses of all sizes. The enterprises that succeed will be those that set themselves up to thrive in any environment. 

  

4.     Act responsibly

It is essential to distinguish between consumer and business usage of generative AI. While consumers can experiment with generative AI without paying too much notice to its inner workings, businesses have a much larger responsibility surrounding risk and security.  They have proprietary data, IP, and sensitive customer information to protect — and ethical, reputational, and regulatory requirements to uphold. 

 

IT leaders understand the need for trustworthy and properly governed-AI. More than 80% of IT professionals agree that consumers are more likely to choose services from companies with transparent and ethical AI practices, but many companies deploying AI are facing barriers in the process. Less than half are taking key steps to ensuring trustworthy AI, including developing ethical AI policies (44%), reducing data bias (27%), and making sure they can explain the decisions of their AI models (41%). 

 

The EU AI Act is progressing through the final stages of the legislative process and, once law, will offer a strong framework for AI governance and usage. Business leaders have a critical role to play in ensuring that the framework is implemented successfully – placing compliance and transparency at the heart of their enterprise whilst driving innovation. 

  

2024 calls for trusted leadership from the private sector — and it will reward that trusted leadership in turn. Good AI is governed AI, and those who hope to lead the charge should instil this principle into everything they do.

  

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Dave McCann is Managing Partner at IBM Consulting Europe

 

Main image courtesy of iStockPhoto.com