We all know that artificial intelligence is going to grow – and technology budgets are changing accordingly. IDC expects the shift in IT spending towards artificial intelligence will be rapid and dramatic, impacting almost every industry and application. By 2025, Global 2000 organizations will allocate more than 40% of their core IT spending to AI-related initiatives, leading to a double-digit increase in the rate of product and process innovation.
But I see 2024 as the year that organizations will start prioritizing the business value of AI. Most of today’s AI applications are Large Language Models or Gen-AI for text and images – bringing a host of quirky and humorous consumer applications. When looking at their own AI priorities, organizations need to focus on value for their external AI product enhancements, but also every tool they use internally can have AI enhancements that will deliver business value. However, these add-ons will increase subscription prices – sometimes even doubling the cost of the tool per user.
Clearly, there is a balancing act that needs to happen to get the cost/benefit ratio right so that organizations get real business value and don’t waste money.
Prediction 1: AI is produced for intelligent applications – but it must get the right data
In 2024, we will see AI and data being “manufactured” into Intelligent Applications to deliver real business value and intelligent insights. Gartner defines intelligent applications in its strategic IT trends for 2024, as consumer or business applications that are augmented by artificial intelligence and various connected data from transactions and external sources.
But in the world of AI-Everywhere, data is a key asset to power AI models and applications. Data collection is currently underway.
Two challenges on the road to big data collection – silos mean silos of data!
Technology vendors and service providers recognize this and will accelerate investments in additional data assets to improve their competitive position. This is much needed, as IDC reveals that only 12% of enterprises connect customer data across departments, and 42% of enterprises underutilize data.
…and needs Unified Control
Making AI and data work together requires a connected enterprise and unified control. IT teams in the next few years will need to begin maturing control platforms as they evolve from a few core systems to becoming a single platform that manages operations across infrastructure, data, AI services, and business applications and processes.
That means running the data – directing the right data to the right places and getting it anywhere in the world.
Prediction 2: The event web is key: Data movement + AI are what truly enable intelligent applications
In 2024, organizations must move from pure “generation” of data to “velocity” of data and decision-making. This requires an event network, a network of interconnected event brokers that allows event information to be distributed among applications. Using an event network allows AI inferences to be layered on top of each other, gradually adding intelligence.
To explain, let’s consider a practical application that combines AI with an event network to react to the analog nature of the world to process and respond to various inputs such as audio, video, and human text.
Imagine an incident management application in a building that monitors a company facility. Security guards are present in the building, as well as security cameras, in order to properly respond to events that occur in the facility. But there are also observers and employees who can send messages or send critical information to the building manager.
AI agents, each performing a specific role, can subscribe to events from these inputs to transform them into more consumable events. Within this network, these inputs will be taken and passed to the appropriate model based on a hierarchical event-by-event description. So, let’s say that the security guard radioed that there was a problem at the reception. It is useless for an incident management application. However, if you push it through the speech-to-text model, expand that event with the actual text that the security guard used, it will then redirect to the incident manager who now has a textual description of what the guard was saying.
It could then use an AI Large Language Model (LLM) to decide what action should be appropriate for the problem at hand. Some of these actions may need to be spoken verbally, in which case it can be directed to a text-to-speech model that can then be played back on the security guard’s walkie-talkie. Of course, that information is augmented and passed through this incident manager, which is all powered by AI. It can then be published to the event network to automatically trigger the next steps, such as turning on the alarm, turning off the alarm, or alerting emergency services to deal with any incident that may have occurred.
The important thing here is that the event network, combined with artificial intelligence, translates a series of analog events into a directed flow of information, allowing extremely fast information acquisition. As the example shows, the business value can be enormous.
Prediction 3: 2024 will see the rise of the Platform Engineer, accelerating the delivery of application business value
But such applications will be only hypothetical without the possibility to design and develop them at all. That’s why it’s exciting that Gartner sees topics like Platform Engineering coming of age in 2024. Platform engineering is an emerging trend aimed at modernizing the delivery of enterprise software, especially for digital transformation. It’s an approach that can accelerate the delivery of applications and the speed at which they produce business value.
Improves developer experience and productivity by providing self-service capabilities with automated infrastructure operations. It involves the discipline of building and operating self-service internal platforms — each platform is a layer, created and maintained by a dedicated product team, designed to support the needs of its users by interfacing with tools and processes. The goal of platform engineering is to optimize the developer experience and accelerate product teams’ delivery of customer value.
Gartner predicts that 80% of software engineering organizations will establish platform teams by 2026 and that 75% of these will include self-service developer portals.
Prediction 4: AI technologies will be counted on to further shorten software development cycles
2024 will also present an increasing opportunity for the use of artificial intelligence in application development. To what degree is up for debate. Forrester, for example, predicts generative AI bots, or TuringBots as they are called, will play a significant role this year in shortening software development life cycles by 15 to 20 percent.
In my opinion, it will be some time before development teams fully incorporate AI bots into their software development lifecycle. But the spirit is there – there is no doubt that AI technologies, such as generative AI and machine learning (ML), will help software engineers create, test and deliver applications, providing a supporting role in accelerating development tasks.
If anything, I believe that in 2024, development organizations will spend more time viewing their software development lifecycles through AI-tinted glasses, seeking to better assess where current processes are flexible enough to incorporate AI in a way that delivers real value. For example, AI-augmented development tools integrated with an engineer’s development environment to build code, translate legacy code into modern languages, enable design-to-code transformation, and improve application testability.
Prediction 5: The Bonfire of the Silo 2024 – Welcome to the Integrated Enterprise of the Future
But amid the rush for real-time and AI-driven operations, large, diverse organizations will continue to be limited in their ability to achieve optimal business value by relying on a complex mix of legacy and/or siled systems. Remember the IDC statistic that only 12% of organizations currently connect customer data across departments! Exploring constellations agrees, stating that “several businesses have lost their data games.”
Because of this, I believe the onslaught of AI Data will drive greater industry-wide urgency for event-driven integration. This entails combining the data transformation and connectivity attributes of iPaaS with the dynamic choreography of an event broker and real-time event network. Only with this enterprise architecture pattern will new and old systems be able to work together to offer seamless digital experiences in real-time, connecting events across departments, geographies, on-premises systems, IoT devices, in the cloud or even in a multi-cloud environment.
Look no further than a refreshing lager
Consider an organization the size of the international brewery HEINEKEN – managing thousands of business-critical applications in 190 countries. To achieve its goal of being the “world’s most connected brewery,” the company unveiled its EverGreen business strategy, underpinned by a shift to event-driven integration. In the past, HEINEKEN saw hundreds or thousands of point-to-point scenarios, but now they use one-to-many integration patterns, where the application only has to produce an event (such as a beer order) once, and all other applications in the system (production, shipping, shipping, inventory, payments, cloud data lake, etc.) they can just subscribe to what they want to receive and get it when it’s published. By delivering seamless digital interactions across the entire value chain, HEINEKEN has now positioned itself to make smarter, more informed and real-time decisions – an organization that is truly playing at the top of its data game.
AI and business value go hand in hand for more real-time operations in 2024
In 2024, businesses must balance AI hype with business benefit.
We will certainly see AI flowing into new products and solutions on the front end, but these applications need the fluidity of data to meet their full expectations. In the background, there is also potential for AI to influence software development processes, but more work needs to be done before we see AI fully designing applications. Ultimately, AI-enabled or not, we will see more and more organizations develop their APIs and integration strategies to be more event-driven, supporting their journey to really big, real-time operations – getting the right insights to the right people, at the right time. moment place, at the right time.