All work is knowledge work to some extent, but that which is mostly done with thinking and creativity is usually included within the concept of “knowledge work”. Most knowledge workers are relatively well paid and their time should therefore be used wisely. Through automated knowledge work, tasks that are distracting and where employees do not use their time and skills in the best way can be handled.

Antti Nivala is the founder and CEO of M-Files and he predicts what will characterize the development in 2024. The trend is clear around what allows us to avoid information chaos, spend less time on manual tasks and instead work smarter and more efficiently with the help of AI and "knowledge work automation". Here is a selection.

Knowledge management will become more holistic.

We know that employee productivity is crucial to the growth and profitability of companies. We also know that they work best in a focused state where they can be creative, think freely and solve problems. Anything that inhibits that flow creates a distraction from work. In the coming year, we can therefore expect more companies to take a holistic approach to all flows and automate work steps to become more productive.

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By investing more in knowledge work automation, it is also possible to eliminate information chaos and streamline business processes. This ultimately reduces the amount of time-consuming manual work and allows employees to work smarter while offering a better experience to customers.

Integration and data curation will become absolutely necessary.

Lack of integration between systems often prevents information flow and creates silos that artificial intelligence is difficult to overcome. For an AI application to work, it needs access to the data it is going to process. Therefore, in addition to access, organizations must Ensure that AI applications only have access to relevant and accurate data.

In 2024, we can therefore expect organizations to prioritize data integration and curation to ensure they can effectively feed their AI tools with data that gives them an advantage over their competitors.

Ethical AI will take center stage.

Artificial intelligence is now being regulated by governments around the world. A couple of examples are President Biden’s AI Executive Order and the EU’s AI Law, which are intended to provide stability and guidance for the rapidly expanding technology. The mass adoption of AI represents one of the most significant opportunities in business history, and organizations must ensure that they are using solutions that are built on a foundation of high-quality data.

With data quality being a central part of the AI issue, it is imperative to have an ethical approach to AI and understand how big Language Models (LLM) works and where they get their knowledge from. LLM:can be powerful tools, but only if they are based on reliable information. To better contribute to the safe and responsible development of AI, we will see organizations start to treat AI as an intern and consider the outcome as a recommendation rather than instructions. We will also see regular audits and increased human involvement to ensure, as far as possible, that AI solutions are trustworthy.

The era of customized AI assistants is here.

It may take time to see how best to integrate AI assistants into companies toolbox to unleash the full potential. While AI assistants has a variety of uses, in 2024 we can expect vendors to tailor AI assistants for industry-specific, value-adding tasks. This can help employees quickly absorb information and solve tasks with human creativity.

User-friendly AI assistants will become more industry-specific and more personalized. Users can increasingly expect the assistant to understand industry jargon and tailor the response based on their job role and task.

If AI is to be a success, data governance is required.

With AI assistants relying on quality and timely content to provide reliable answers, data governance will be a success factor in the coming year. A common misconception is that you can point an AI assistant at any pile of documents and get reliable results.

But the reality is that content integrated across sources needs to be cleansed and validated for AI to work effectively, so we will see more organizations using metadata in 2024 to gain better data governance.