Technology Trends for 2024: What’s Ahead?

Artificial intelligence

AI and ML were everywhere in 2023, and for good reason. ChatGPT proved to be an incredible tool and easily accessible to the masses. But what does multimodal generative AI mean in the B2B space? Moving from “can” and “could” to “are” seems to be the next big step.

Jethro Borsje, Chief Ecosystem Officer: “I expect the success of AI in 2024 to predominantly come from very discrete, domain-specific applications instead of general-purpose LLMs. With tools like ChatGPT, let’s think about what they can bring business users rather than focusing on consumer applications.”

Subba Rao, Director, Manufacturing Industries Cloud: “In manufacturing, the democratization of generative AI will be huge. Generative AI helps connect disparate sources, digitizing them and then applying large language models to abstract complexity for business users. In 2024, the early proof points, learnings, and real roadblocks will start coming to the surface. That helps platform vendors (like Mendix) identify where there is real ROI in applying generative AI while abstracting data complexity to simplify application development.”

Gordon Van Huizen, Senior Vice President, Strategy: “2024 will be the year where the wave of enterprise innovation through AI hits the shore. Throughout 2023, enterprises moved from investigation and into piloting and experimentation. Not everyone has seen their yield ramp up yet, but 2024 will see the translation of the good ideas into the right ideas and then delivering on them. Organizations bought into concepts like fusion teams and business-IT collaboration will be best positioned to move quickly from idea to production at scale. I’d say the wait-and-see approach is actually riskier than making the investment now. Companies need to move.”

Hans de Visser, Chief Product Officer:  “Organizations will start to answer some of the real questions around AI. How will GenAI and AI impact their way of working? Their business models? Their operating models? There are organizations putting things in place, but no one has totally figured out the use cases. Everyone is interested, and I think low-code will help actualize ideas. Low-code has always helped as an extender of development capacity by adding abstraction and automation. AI helps even more with that, so developers can focus on value adds. Interpreting AI models in high code is a big challenge. But when you bring that into the visual language that low-code provides, it becomes much more accessible.”

Data science and democratization

As the world continues to get smarter and more sophisticated, most organizations are producing more and more data about customers, processes, employees, and more. But more doesn’t always equal better. And without the proper structure and integrations, all that critical data can be meaningless. Organizations need to plan and invest in their data strategy to make it all meaningful

Tim Srock, Chief Executive Officer: “We’re already in a data-heavy space and this year will start to see a lot of pieces come together:  Analytics, AI, task automation, and the democratization of those through things like natural language processing. Without the proper data, none of those things work. Enterprises that are really on top of data and data science will be better prepared to make the triangle of data, app development, and AI work. Enterprises that are really on top of data and data science will be better prepared to make the triangle of data, app development, and AI work.”

Subba Rao: “In an industrial context, we will see data become even more important. A data-driven mindset, data strategies to abstract complexities for business technologists, a common platform,  an ecosystem of partners—these are the tools needed to help  in co-innovating and co-creating purpose-built software solutions across the business.”

Hans de Visser: “There’s a convergence that will happen between the worlds of data scientists and application development. It’s all about turning data into action into insights, and those insights typically go hand in hand with applications.”

Platform consolidation

The average number of SaaS applications companies use rose from 80 in 2020 to 130 in 2022. As businesses look to solve more and more of their use cases, the potential exists for an overload of platforms and fragmented data. That kind of overload can be the downfall of innovation, so enterprises need to be thoughtful in their approach.

Sheryl Koenigsberg, Vice President, Global Product Marketing: “This is the year that CIOs ‘Marie Kondo’ their technology landscapes. Remember that trend where people would look through their homes and closets and discard the things that ‘didn’t serve them anymore’? This year, IT organizations, weary from years of patching together transitional tools and emergency investments to solve point problems, will finally get a handle on their technology clutter. With technical debt consuming up to 40% of specialists’ time and the proliferation of technologies making for an expensive and complex collection of investments, CIOs will truly evaluate platforms and capabilities and carefully weed out and retire those that no longer solve their most urgent problems. Instead, they’ll focus on general-purpose platforms that serve a broad set of capabilities and are accessible to people with a wide range of technical acumen.”

Nick Ford, Chief Growth Officer: “Many businesses have looked to solve particular problems with very specific platforms and solutions. But when you want to build complex systems that play outside of those ecosystems, those solutions can’t talk to each other or share components. 2024 will see more organizations move towards “platform of platforms” that smaller solutions can roll into. Easier to maintain and iterate on, easier to innovate, clearer path to success.”

Jethro Borsje: “I see composability as part of how organizations look at themselves and how they use software to digitize their processes. Part of that is growing their ecosystems to leverage specific capabilities from third parties without having to own everything themselves. That makes their organizations more agile and increases their ability to respond to change.”

IT governance and security

Governance and security are critical. That’s not controversial, but they’re topics that enterprises of all shapes and sizes struggle with constantly. Opportunity exists for those platforms and enterprises that can make governance easier and more agile.

Sakshi Dhakad, Senior Product Manager: “Enterprises want to better manage digital chaos based on their risk apertures. Customer needs range from rich visibility into their digital landscape to intelligent tooling to detect anomalies and optimize costs. Lack of essential governance capabilities is already a non-starter in the market. The more malleable, automated, and intelligent approach enterprises take to governance, the more returns they can expect. For instance, using policy-based automation to shift left, reduce operational load, and ensure quality software. Another example is using adaptive forms of governance guardrails so they can be adjusted based on business needs and continuous learning in-platform rather than having to orchestrate large-scale change management programs. Low-code platforms, like Mendix, embed the essentials and provide a simplified abstraction to govern a landscape when compared to high-code. This will become more pronounced in 2024 as governance becomes more important.”

Hans de Visser: “You can see a wave of shadow IT with development happening by data scientists outside the usual structure. These are brilliant, creative people building solutions that lack governance because they’re in a domain that corporate IT doesn’t always touch. Think about the risks to those data science outputs: employee turnover, security, and compliance. As this grows, there’s a serious opportunity for data scientists to be able to work with enterprise data in full governance and transparency, along with all the tools and mechanisms for serious app development.”