The real battle for generative AI in software
The key to AI success is meeting consumer demand
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When it comes to technology, we often credit the companies creating the tech as those driving disruption. But the real power behind big innovations? The consumer. Just like the rise ofmobiletech was fueled by everyday users, the explosion of generativeAIcan be traced back to the consumers who actually use it. The presence of Gen AI in B2B started when people asked, “why can’t I have that at work?” In many cases, Gen AI took off in the workplace because it took off at home. WhenOpenAIreleasedChatGPT, it wasn’t just a shiny, new gimmick – it was a game-changer that sparked a wave of consumer interest, and one which quickly caught the attention of businesses everywhere. And while many companies have been working in the Gen AI space for years, the push from B2C really accelerated this technology in the B2B space.
What makes Gen AI so appealing is that it’s something people can easily understand and use. And it’s amazing. Gen AI has captured the imaginations of consumers and businesses alike. As tech giants like OpenAI,Google, andMicrosoftlook to weave Gen AI into their products, the real fight isn’t just about who can build the most advanced AI, but who can keep up with the growing consumer demand.
Software companies are now in a race to roll out Gen AI features as fast as they can. But the real challenge lies in meeting the expectations of employees and customers who are eager to see the benefits of AI in their day-to-day lives.
With that in mind, here are my top tips on how companies can stay ahead of the curve in this fast-paced, constantly shifting environment.
Global High-Tech Industry Leader for Capgemini.
Empower your developers
The heart of any software company is its developers. Gen AI offers a boon to supercharge their creativity andproductivity. By providing developers with access to the latest AI tools, organizations are not just enabling them to automate more mundane tasks like code generation, documentation, and bug fixing—but are also unlocking their potential to tackle bigger, more complex issues.
This has also unleashed improvedcollaborationbetween tech and business teams. From better communication to explaining what the code is doing in natural language; Gen AI makes the connection between software engineers and other business teams more effective. In fact, 78% of software professionals are optimistic about Gen AI’s potential to enhance collaboration.
Gen AI can even act like a brainstorming buddy, tossing out ideas and solutions that might not have crossed your developers’ minds yet. This collaborative vibe speeds up the rate of development and keeps teams on their “A” game – as well as providing opportunities for consistent learning and improving. As developers get more comfortable with AI, they’ll push the boundaries of what’s possible, an all-important competitive edge in this evolving landscape.
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Data remains king
Software companies have another huge advantage when it comes to Gen AI in that they own theirdata. The more structured the data is, the easier it is to train against it. This gives software companies an advantage in providing Gen AI around their services. The more features a customer can get, the more likely that customer is to buy into a company completely.
Imagine a life insurance company has built itsCRMsystem around a particular vendor, its data repository off a different vendor and those disparate systems don’t connect. How can this life insurance company leverage Gen AI? Well, if the CRM vendor has all this structured data around thecustomer, it can create and provide great Gen AI features where the client doesn’t need to go anywhere else to tackle the challenge of disparate data. They can get all the Gen AI features they need from their CRM vendor, thereby eliminating the need for the data repository vendor. That’s a major competitive win for the CRM vendor. It’s a race, and our take on the race is that we want to empower our clients’ developers to work better with Gen AI so they can do all these things faster and we want to work with CIOs to help them use Gen AI internally faster to pave the way. It’s all about finding the right balance between speed and relevance, paired with developer productivity against structured data.
Transform your processes with “Agentic Roles”
Bringing generative AI into your business isn’t just about making things more efficient – it’s about transforming how you work. By embedding it into day-to-day operations, organizations can streamline workflows, cut down on manual tasks and make smarter decisions faster. Think real-time data analysis that provides instant insights and helps talent make better calls in areas like customer service, supply chain, and product development. But what was thought about as a process in the past now must be thought of as a series of Gen AI Agents serving the role of key human decision makers along the way. This is re-engineering on steroids.
Automating repetitive tasks with AI doesn’t just save time – it can also save money. And with those extra resources, companies can begin to focus on more strategic, fruitful projects. The trick is to not see AI as a separate part of the tech stack, but as a new way to work.
Adopt a platform mindset
In the rush to adopt AI features, it’s easy to think of Gen AI as just another tool in the box, but to really unlock its potential, enterprises need to think bigger—adopt a platform mindset. This means seeing AI as the foundation that supports and enhances all your products and services, not just a one-off feature. AI can be the moment in the sun for VPs of Engineering and Platforms. No longer are they a forgotten enabler to get features to market, but they ARE the future of the business.
A platform mindset encourages the development of AI-driven solutions that are scalable and adaptable across different areas of your business. Defining the work you do through Agents cements this role. This approach not only helps create versatile platforms that deliver long-term value but also ensures that AI is smoothly integrated into the entire value proposition of your organization. By thinking in terms of platforms instead of solely products, organizations are better equipped to meet the evolving needs of their customers and stay ahead in the AI game.
The real battle for Gen AI in software isn’t just about who can build the best tech—it’s about maintaining momentum in a sea of mounting consumer demand. Companies that empower their developers, transform to agentic thinking, and adopt a platform mindset won’t just keep pace with this demand—they’ll lead the charge in this new era of innovation. Those that come out on top will be the ones who understand that generative AI isn’t just about making cool products—it’s about driving real, meaningful change that resonates with both businesses and consumers.
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Brett Bonthron is Global High-Tech Industry Leader for Capgemini.
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