The top 7 BI trends, big data trends & AI trends of 2023
We still have to bite through the bitter apple. Turbulent geopolitics with military might, a new cold war, mega-inflation, an (imminent) recession and the accumulation of crises, some of them self-inflicted, threw a lot of spanner in the works last year. With this predominantly negative sentiment, it is surprising that the IT industry still managed to pull promising AI and BI technology out of the hat this year. As always, Passionned Group reviews the latest big data-based trends for you for relevance, feasibility and practical applicability. We hereby give you the most important BI, AI & Big Data trends.
- ChatGPT surprises the (information) world
- Government will strictly regulate AI and big data
- Data governance becomes hygiene factor
- AI Powers Digital Immune System
- Big data solves world problems, but...
Welcome to the new reality
Trend 1: Revolutionary ChatGPT turns information world completely upside down
Last year, we noticed that Artificial Intelligence (AI) is still too abstract for many people. In the coming years, AI will offer increasingly concrete solutions, in the medical and financial sectors, but also in marketing, communications and customer contact. Currently, ChatGPT is absolutely making waves with a, according to Elon Musk, “frighteningly good chatbot” that is rapidly taking the world by storm. ChatGPT allows you to request information and inspiration in plain human language. ChatGPT also helps fix software bugs and generates computer code itself. That makes the application very interesting, especially for novice software developers. But there are more “mindblowing things” you can already do with ChatGPT, according to early adopters.
With ChatGPT, conversation flows many times more naturally
With that at least, the “prehistoric” chatbots seem doomed. For the technicians among us, ChatGPT 3.5, stands for Generative Pre-trained Transformer and is an open-source application of OpenAI. The chatbot uses Reinforcement Learning with Human Feedback (RLHF), a form of deep learning. Although there are still some limitations (for example, the training data has been updated to 2021, so current information is missing), ChatGPT looks promising and could well become a formidable competitor to Google’s search engine.
We took the test (“just for fun”) and asked Dall E, another AI application from “the stable” of OpenAI, to automatically generate an image of a sports car spray-painted in the style of Van Gogh. You can see the stunning results of this little Generative AI experiment in Figures 1 to 3.
Trend 2: Governments are pulling ever tighter reins around AI
So as technology advances, European and national governments are pulling the reins around AI ever tighter. Explainable AI, in which algorithm-based decisions are explained to citizens and other stakeholders in a transparent and understandable way, is a trend that is sure to continue. Large municipalities such as Rotterdam, The Hague, but also independent administrative bodies and implementing agencies such as the UWV and the Tax Office are reluctantly publishing in algorithm registers which algorithms they (all) use: rules-based or self-learning algorithms. The central government is considering appointing an algorithm supervisor and is also working hard on an umbrella website: The Dutch government’s Algorithm Register, a database that is still under development. Citizens should be able to keep control of their digital lives and also be able to trust the digital world (read: algorithms), is the premise.
AI Act is going to regulate AI far and wide
Legislation and regulations surrounding AI applications are also gaining traction at the European level. For example, European telecom ministers reached agreement Dec. 7 in Brussels on the so-called artificial intelligence regulation, the AI Act, which totals 108 pages. The AI Act is a risk-based approach to start far-reaching regulation of artificial intelligence. Only AI systems with no or minimal risks will be tolerated without restrictions. Some algorithms will be flatly banned after review.
The regulation covers all forms of AI, including machine learning applications and all possible hybrid models. On this AI Act, the European Parliament and the European Commission will now continue negotiations. They are aiming for a final agreement in the fall of 2023, after which member states must start implementing the regulation domestically. Let us hope that AI startups will not be discouraged by this new form of bureaucracy and will continue to invest in innovative applications, such as ChatGPT.
Trend 3: Data governance is becoming the hygiene factor for data-driven work
Last year we signaled that the traditional data warehouse has lost some of its luster. On the one hand, this is due to the fact that new stars have appeared in the firmament, such as a data fabric, a data lakehouse and a data mesh. On the other hand, organizations are still struggling with their data governance. Organizations these days first start experimenting with BI and dashboarding to get users used to all the dashboard and analysis capabilities, only then do they start scaling up, our consultants observe with clients.
DAMA framework remains leading
Intuitively, most managers know that data governance is crucial to achieving success with business intelligence, but applying the total of 11 knowledge fields of the so-called DMBoK model version 2 of The Data Management Association (DAMA), that’s another matter. Which CIO, controller or auditor dares to put his hands fully in the fire for this? Inconsistency of different data sources, incomplete data and failure or inadequate sharing of crucial data between different silos means that many opportunities remain unexploited and current BI programs fail. It also leads to several versions of the of the truth circulating in many organizations instead of just one.
With the advent of AI and data-driven work, it becomes even more essential that organizations get their data governance in order. The Dutch section of the DAMA gives organizations a (small) helping hand in this regard and announces to take up the Dutch translation of the DAMA DMBoK framework.
There will finally be a Dutch translation of DMBoK version 2.
But even without that translation, organizations will have to get to work themselves and invest in a data architecture, data storage, data security, data integration & interoperability, metadata, data quality and so on. It’s the only way to force a real breakthrough with BI, as Forbes Insights and Qlik noted back in 2016. Unfortunately, there is no perfect formula, but finding the right level of governance within your organizational culture is crucial to get as much value as possible from not only BI and AI, but also data-driven work.
Trend 4: Adaptive AI takes off in the coming years
Adaptive AI, unlike traditional AI systems, can make interim revisions to its own code to adapt to changes in reality that were not known or anticipated when the code was first written. Adaptive AI does not come completely out of the blue. Philips, for example, introduced the concept of adaptive intelligence, or technology that takes into account the user and the specific context, several years ago. And in education, adaptive learning, a form of online, personalized learning using artificial intelligence, is already fairly well established.
More examples of adaptive AI
In adaptive radiotherapy, for example, the technology takes into account changes that may occur in patients during treatment. This is because it is a major challenge to give cancer patients the right dose of radiation with each treatment, in the right place with the least damage to healthy tissue. After all, patient and tumor are constantly moving and changing shape over time. ‘AI outperforms the pathologist, but together they are even better,’ Radboudumc researchers conclude.
In the manufacturing industry, adaptive support systems provide customized work instructions. According to the National AI Coalition, adaptive artificial intelligence is deployed to directly utilize measured data from the process (productivity, human errors) and operator feedback. Employees receive customized work instructions and therefore appropriate to their level of knowledge and experience. When you log in as an employee, the AI algorithm selects the instruction level that best matches this operator’s work experience and characteristics based on historical production data. If you are just starting out and are inexperienced, you will be shown instructions at each assembly step. A camera monitors product quality.
Adaptive AI can also be used to continuously improve the customer experience in every interaction between a customer and a brand. AI-driven chatbots will continually refine their conversational skills, and recommendation engines will become more sophisticated, making recommendations that really resonate with customers.
Trend 5: Digital Immune System is increasingly driven by AI
To prevent business disruptions and downtime of systems and machines, organizations should start investing in a Digital Immune System (DIS). This will allow them to reduce downtime by 80% and optimize customer satisfaction as early as 2025, according to Gartner, it sounds optimistic. Nevertheless, a DIS remains a somewhat abstract model. As far as we are concerned, we therefore extend the scope of such a digital immune system to cybersecurity.
Cybercriminals benefit from chaos
IBM now recognizes threats up to 50 percent faster with its AI platform Watson. One way Watson does this is by automatically extracting trends from large amounts of documents, blogs and news articles in seconds or at most minutes. An expert then receives an alert about malicious software files, suspicious IP addresses or hacker behavior, among other things. Nevertheless, the threat from cybercriminals remains high as they keep finding new targets. This year, the “Manufacturing” sector was the hit, according to IBM’s latest threat index. One thing is certain, cybercriminals are benefiting from the current economic and geopolitical chaos.
Self-healing software has the future
For its part, TNO is trying to apply principles from biology and immunology to cybersecurity with a special research program. What can we learn from the human body’s defense mechanisms against attacks by viruses and bacteria? While the human body regularly replaces its own biological cells, in IT a very different principle applies: if it aint broke, don’t fix it. The trick, according to the researchers, is to build a system that is decentralized and self-repairing. The open source Kubernetes system could well play a leading role in this. ABN AMRO is already using self-healing software for cyber security.
Cat and mouse game
Another concrete example. How do you recognize deepfakes? The Netherlands Forensic Institute (NFI), together with the University of Amsterdam, is introducing the rolling shutter method. This allows you to determine the time and place of a video. You can tell from the light in the background of a fake video that something in the recording is not right. In addition, the NFI uses Photo Response Non Uniformity (PRNU), a kind of fingerprint of the camera of your phone. This allows you to determine which camera the images were taken with. But criminals don’t sit still either and often have deeper pockets to purchase the latest gadgets. In short: The fight against cybercrime will continue to be a cat-and-mouse game in 2023.
Trend 6: Big data remedy for world problems, but kills privacy
Big data and data analysis have the potential to help solve major world problems, according to the recently founded Analytics for a Better World Institute (ABW), an initiative of University of Amsterdam, U.S. MIT and ORTEC. Reducing poverty, combating climate change and better healthcare, the founders of the ABW are convinced that analytics can play an important role in finding solutions, as data analytics has already been successfully applied by commercial companies and it has improved performance by 10% to 15%. Central to this are the 17 Sustainable Development Goals of the United Nations.
The KNMI Datalab also firmly believes in big data. The meteorological institute contributes its own source data and shares knowledge with clients and partners with the aim of adding value. For example, the combination of high-resolution weather data and traffic data can improve traffic flow and traffic safety. And by analyzing camera images along highways, the institute can improve fog detection and fog forecasts. Rijkswaterstaat is now collecting so much data that they have their own nationwide fiber optic network.
Sustainable by design is the new mantra
By 2025, 50% of CIOs will link their KPIs to the sustainability of the IT organization, Gartner predicts. Dubai Electricity & Water Authority, for example, uses IoT and digital twins to create smart building management solutions that use 50% less water. Apple uses robots for recycling. And Timberland encourages employees to personally participate in sustainability initiatives. “Sustainable by design” is the new mantra, but window dressing is always lurking.
For example, Zembla recently showed that multinationals have failed over the past 30 years to make plastic packaging of fabric softeners, among other things, lighter and therefore use less plastic. Also, while many plastics are theoretically recyclable, often only 50% of packaging is actually reused. And in the final design of packaging, the marketing manager has a heavier voice than the sustainability manager. Regulators will therefore pillory and fine companies that engage in greenwashing and project a green image, Forrester predicts.
But “Data for Good” also has a dark side: apps invade our privacy. It is not for nothing that advocacy and action groups such as Privacy First and Bits of Freedom are protesting smart energy meters, camera surveillance, biometric applications, vaccination certificates, UBO registers, route controls, the Sleep Act and so on.
Mass surveillance is the deathblow to our privacy
That mass surveillance is the death knell for our privacy is aptly demonstrated by Dave Eggers in his book The Every. Algorithms at The Every – a fictional company that closely resembles a mix of Facebook, Google and Apple – periodically determine which 10% of employees will be fired. Apps and devices measure and know really everything. For example, they record whether you exercise enough, are socially interactive, how you treat your co-workers, whether you use “appropriate” words, whether you are honest with your friends. Your aggregated “shame score” tells you whether you are doing well. Also in the book “The Intelligent, Data-Driven Organization,” you’ll find several elaborate examples where “data for sustainability” makes a difference.
Trend 7: Low-code and no-code are the future
In the field of software development, the low-code-no-code movement, abbreviated LC/NC and not to be confused with “Low Class/No Class,” is on a long but steady march. By 2024, 80% of technology products and services will be created by people who are not technology professionals (also called “citizen developers”), Gartner predicts.
This evolution or democratization of software development is made possible by, among other things, the growth in digital data, a wide range of low-code development tools (drag-and-drop), low-code platforms and, last but not least, artificial intelligence (AI).
Pros and cons according to ChatGPT in 150 words
We asked ChatGPT (see trend 1) to summarize the pros and cons for us (“Name the most important pros and cons of low code and no code in up to 150 words”). Within seconds, we got this answer in 217 words. A little too many words, but apparently nothing human is alien to ChatGPT….
ChatGPT: “Low code is a technology that allows software to be built by using visual interfaces and user-friendly drag-and-drop tools, rather than requiring programmers to manually write code. This can help build and maintain software faster, especially for organizations that don’t have access to a large engineering staff or want to respond quickly to changing business needs. One disadvantage of low code is that it may not be as flexible as manual coding, and the resulting system may be less efficient or less robust. In addition, it can be difficult to implement complex or unique functionality with low code.”
“No code is a step beyond low code, making it possible to build software even without any technical knowledge. This can help lower barriers for people who want to start building digital products or services, and can also help develop and test prototypes quickly. One disadvantage of no code is that it may not be suitable for more complex or large projects, and the resulting software may be less flexible or less efficient than software created by professional programmers. In addition, it can be difficult to get good support or help when using no code tools.” End quote ChatGPT. In the Netherlands, municipality of The Hague and Rotterdam, Post NL and Rabobank are leaders with low code software development.
While the drones buzz around above the battlefield, there is a glimmer of hope. Hope for a constructive peace negotiation. In 2023, let’s use technology in a positive and constructive way for a better, more just and sustainable world. Passionned Group’s management, content team and partners wish you a prosperous new year.