It is not without good reason that analyst IDC’s Aly Pinder, VP of Aftermarket Services Strategies, summarizes IFS’ capabilities when it comes to AI and related pieces like this: “IFS has a strength in the breadth of service capabilities that include AI, machine learning (ML) and IoT,” Pinder notes, which is well in line with assessments made by other prominent members of the analyst community, such as Gartner and IDC.
It is clear that AI and ML, Machine Learning, have generally been a key in ERP development in 2024. With AI-based functionality, we have seen major changes. We are talking about important tools that enable companies to centralize data management and create comprehensive analyses across the business. No one needs to think very long about the value that comes with an industrial ERP system that connects all aspects of an organization, a system capable of drawing well-balanced conclusions, that standardizes and automates processes. A reasonable outcome of this is a significantly sharpen operational efficiency.
“A Fundamental Change to the Way We Work”
But how big is this AI? IFS CTO, Dan Matthews, is clear about the matter: “It’s really big,” he says, putting AI technology in a historical context.
“AI will fundamentally change how the world works and how we work. The technology creates enormous opportunities, of course, but can also seem a little scary, just like all great technological advances always have.”
But why is all this happening now; AI has been around us in various forms since the 1950s, he asks rhetorically.
“Let’s first state that this is not the first time that new technology has changed the world. When I was a kid, I had one of those little steam engines that you fed with meta tablets, but steam technology as a principal were actually invented sometime during the first century of the modern era. However, it was not until 1500 years later that people started using steam engines to pump water out of mines, and in the 18th century under James Watt, the machines were used in the manufacturing industry. Then their use grew like an avalanche, steam locomotives, steam ships, steam hammers in the metal industry – the development ended in a general industrialization based on steam, which was everywhere. It was, in short, the heart of the industrial revolution. But this development is by no means unique. We can see similar industrial technological development sequences in telegraphy, telephony, computers, etc. It is interesting to see how we humans have taken up, learned and finally embraced all these new technologies and from this created a more productive and better society as a result. AI has the same dramatic effects on our society right now.”
A Historically Pedagogical Approach
It is undeniably an elegant pedagogical approach that Matthews takes to put AI in a historical context and to connect it with IFS in the next breath.
He is rightly proud of what he and the development team has created, a platform that they also continuously are refining with the ultimate objective to attract all of the company’s customers in industrial business systems to quickly adopt.
“We have done this well,” claims the IFS’ CTO. “Our system has been developed to provide autonomous decision-making capabilities in real time, which goes beyond predictive analysis in areas such as production scheduling and supply chain optimization,” he says, adding that AI is now drastically transforming business operations. “AI is embedded in IFS Cloud and it makes a huge difference. We have the AI agents, we have the copilots, and what we are now seeing is how we are next moving into agentic AI.”
Copilots in this context are virtual assistants powered by AI to guide and assist users, thereby increasing productivity and efficiency across all workplaces and environments. Also worth noting in the reasoning is the difference between “agentic AI” and “AI agents”: Agentic AI can be seen as the framework; while AI agents are the building blocks within the framework.
Agentic AI uses sophisticated reasoning and iterative planning to autonomously solve complex problems in multiple steps, asserts Matthews, stating that it delivers personalized and responsive experiences at scale and speed. Using sophisticated models, AI agents can infer customer intent, predict needs, and offer tailored solutions, all while working 24/7 to ensure consistent and effective support.
AI Agents Are Key
Hence, IFS’ CTO’s conclusion is that we are now moving towards agent-based AI, and AI agents play a key role in the process. They are programs that can interact with their environment, collect data, and use that data to perform self-determined tasks to meet predetermined goals. Some agents work solely with predefined rules, while others use learning algorithms to refine their behavior. Humans set goals, but an AI agent independently chooses the best actions it needs to take to achieve those goals. They can do what needs to be done better, faster, and most importantly, cheaper than things have been done before.
There are five main types of AI agents: Simple reflex agents, model-based reflex agents, goal-based agents, utility-based agents, and learning agents.
“The emergence of AI agents that can handle complete business tasks across different parts of an enterprise system is really one of the keys to effective AI and represents a transition from simple automation to more complex, context-aware actions. We want our system to be a bridge between all these amazing islands of opportunities that AI can connect,” Dan Matthews says.
“We can do the heavy lifting for our users by innovating, embedding, and making this technology available to our existing IFS community and potential customers. We do it in the IFS Cloud and it’s a out-of-the-box setup. It’s the heart of our product strategy,” he adds.
How Does the AI Evolution Continue?
Dan Matthews further explains that IFS Cloud is serviced by the IFS AI platform, which metaphorically sits like an umbrella over IFS’s flexibly composable functionality modules. In all of them, IFS.ai capabilities are embedded virtually everywhere.
The revolution is already a fact, he says, but how does the AI evolution continue?
“Overall, the development looks like this: Predictive AI has been around for a long time in the business systems world to forecast, schedule, optimize and create insights that were previously not possible. A few years ago, generative AI came along – artificial intelligence that can generate text, images, videos or other forms of data using generative models, often in response to specific instructions. It was the best language interface to computers that humanity has seen so far. It helps us interact with systems, ask quick questions, summarize, describe, articulate, translate and improve so much in our handling.”
“But now that we are moving towards agentic AI,” he continued, “it is no longer really about just making individuals, people more productive, but also entire companies and businesses. They will become more efficient, faster, more flexible and highly automated. With agentic AI we get these much talked about digital workers – agents – who can take in special goals and tasks, break down problems, reason about what is right to do. While we humans in parallel are in the decision loop for final approvals of actions, or to be guided and get the advice we have asked the agents for.”
This is something that Matthews claims is just around the corner and something that IFS intends to provide to users via IFS Cloud.
Five Reasons Why IFS AI Stands Out in Competition
But what makes IFS stand out when it comes to AI? Matthew points out five points:
- To a greater extent than its competitors, IFS.ai is always contextual. It delivers critical contextual analysis from the data ecosystem within IFS Cloud. Getting the right information to the right people at the right time ensures that teams are informed and can focus on what matters most.
- It is secure and private
- It is embedded in the system in a turnkey manner
- It is a reliable, explanatory and ethical AI
- It is built on embedded, open, flexible and extensive capabilities
That said about the overall AI pieces; in an upcoming article we will go more hands-on together with IFS’ senior VP, Martin Gunnarsson.
On the Bottom Line…
The future looks bright for IFS. Partly because it operates in a market (ERP) that is set for growth and which in 2024 was valued at $81.15 billion. By 2030, the market is expected to increase to be worth just over $238 billion.
IFS works globally in this growth market and has a number of strong global and local consulting partners in its ecosystem, like Accenture, Tech Mahindra, and Tata Consultancy Services.
Furthermore, the reasons why the global demand for ERP increases can be related primarily to increasing business complexity, the need for global business continuity, stricter regulatory requirements and changing customer expectations. In this, AI, machine learning and cloud technology act as enablers, allowing ERP vendors to help its customers improve automation, scalability and adaptability in response to these market pressures. IFS has tools ready, or in the pipeline, tools that are characterized by capacity, ease of use, quick implementation and scalability.
