Three approaches to generative AI: which approach will you choose?
Generative AI is predicted to have a huge impact on the way we work. According to research from Accenture, three-quarters of UK workers could have at least a third of their working hours affected by GenAI, with their working patterns and behavior taking advantage of this technology. But while there is much discussion about how this technology could be used, there is no consensus on how well companies will adopt this technology. In the same report, only 33 percent of respondents expect business leaders to be responsible when it comes to AI decisions and make the right choices to have a positive impact.
Why does this matter? Accenture estimates that not using AI or using it poorly could lead to an opportunity cost of £485 billion in economic value by 2038. This is a bigger opportunity for Britain than any other G7 country and could almost undermine Britain’s long-term chances double. growth rate over time within 15 years.
Whether these numbers are accurate or not, the overarching message is that using AI delivers more potential value than not using it. So how can we determine the right strategy to take advantage of AI, and what choices will be involved?
Head of field engineering for EMEA at DataStax.
Strategies and priorities
GenAI follows other important technology trends and changes. From the move to client-server applications, across the web, cloud and mobile, companies have experienced large-scale changes, from new ways of working to changing markets. For example, the move from high street shopping to online and mobile commerce had consequences for many businesses, with some embracing an online approach, while others waited and saw their market share decline.
For GenAI, business leaders appear to be taking one of three approaches: delegate to GenAI, accelerate with GenAI, and reinvent businesses on top of AI. Each of these has its own mindset and approach to business impact.
Delegate to GenAI
Using AI to delegate tasks focuses on how GenAI can take over tasks currently performed by humans. GenAI replaces those people in their jobs, and the workforce is then reduced as AI is introduced. The overall goal of this approach is to reduce the cost of providing a service to customers by a certain percentage (say 30 percent) and leverage this reduction. to improve profitability.
Accelerate with GenAI
For the Acceleration approach, business leaders are still looking to GenAI to reduce human input and take over tasks. But instead of immediately throwing those staff overboard, companies can look at how they can use those skills elsewhere. This approach uses AI to find more revenue growth opportunities, improving productivity and profitability through more effective execution. Instead of cutting costs by 30 percent, these companies use that money to increase their overall revenue and profitability together.
Reinvention
The third strategy – Reinvention – goes one step further. While the Delegate and Accelerate strategies can be implemented by any company, the Reinvention approach is more difficult for established companies to adopt. It starts with the proverbial blank sheet of paper and is based on asking the question, “How can I use this new technology to deliver that service better and more effectively than the traditional companies that came before me?”
Instead of looking for cost savings or more improvements to existing models, these companies are looking for completely new approaches to the market that can deliver much greater results. Every new wave of technology involves companies. For the Internet, the biggest example is Amazon, which used the online model to compete with brick-and-mortar retailers. It is now worth $1.94 trillion, based on a combination of customer focus, competitive pricing and market expansion. Similarly, companies like Uber and Instagram built on mobile apps to create new apps that would fundamentally change the markets in which they operate and support millions of customers.
To reinvent a business approach with GenAI, companies don’t have to think about how to add AI to their existing application. Instead, the starting point should be how the delivery of a product or service can be tailored to meet customer needs, with GenAI at the heart of this approach.
The potential opportunities surrounding business reinvention are enormous. Sonya Huang and Pat Grady of venture capital firm Sequoia point out that AI – and agent AI in particular – is taking over services markets, rather than just looking at the technology product sector associated with that service. Instead of Software as a Service, they call this “Service as a Software”. The goal for companies here is to dominate in markets that are much larger than software or technology alone, and that previously relied on people and their skills. Instead of looking at the $3 billion market for AI software, companies should look at the $10 trillion market for services.
In today’s world, the Reinvention approach means looking at AI and then looking at how to structure a business, rather than the other way around.
Is your decision the right one?
Whatever your business, you’ll need to think about strategy and how to make the right choice around GenAI. You also need to be realistic about your goals and how you can achieve them. It’s also important to note that many companies will change their approach to AI over time. Many CEOs and boards of directors will decide that they want to create companies that follow the Accelerate path, but after some initial wins they will then retreat into the Delegate category.
Furthermore, GenAI is still an emerging technology and companies are figuring out how to scale their projects. Approaches like augmented generation retrieval make it easier to embed business data into GenAI applications or services, but that data has to be good in the first place. According to Appen’s 2024 State of AI report, GenAI usage in enterprises has increased 17 percent year-over-year, but there has also been a 10 percent annual increase in issues surrounding projects due to data quality.
Without data there is no AI. Without good data, there is no good AI deployment that can take over a role or deliver performance improvement, let alone base a whole new business on it. Understanding the entire approach around AI and data, and how these services work in practice, is necessary to achieve strategic goals for the business.
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