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When to introduce AI to enhance your traceability journey

AI is a powerful tool. In this blog we explain how Interu is using it to help streamline operations, enhance decision-making, and boost productivity, but also when human judgement should not be replaced.

AI vs human judgement

Artificial Intelligence (AI) is more than just a buzzword; it's a transformative force reshaping how businesses operate and innovate. In recent years, AI's prevalence in enterprise settings has soared, with Statista reporting that over 37% of businesses and organisations have adopted some form of AI as of 2020. This figure is expected to grow exponentially, with PwC predicting that AI could contribute up to £12.56 trillion to the global economy by 2030.

This burgeoning interest is not unfounded. AI offers unprecedented capabilities that streamline operations, enhance decision-making, and boost productivity. However, it is important to note that AI should not replace human judgement, and instead be seen as a co-pilot, or an assistant in helping make your life easier. 

AI-enhanced traceability: The future is now

An example of AI's potential can be seen in its application within traceability systems, such as iov42’s solution, Interu, a leading technology in ensuring the integrity and transparency of supply chains to help towards compliance, improved efficiency and to save time (and money).

We know that at present, a large number of organisations are still using excel spreadsheets to store and share their data. This just isn’t scalable. With incoming deforestation regulations, like the EU Deforestation Regulations, the amount of data required to conduct the necessary due diligence to meet compliance will only increase. A concern for 56% of EU timber Operators according to our recent Deforestation Regulation Readiness survey

Interu is already helping its users to securely store, manage and share data to help towards compliance, and we are exploring what the future might look like for our users with the introduction of AI to help manage the scale of data and conduct risk assessment. For example: 

  • Automated Translation of Documents: AI-driven translators have matured significantly, especially with the advent of Transformers models in 2023. These systems offer mature translation capabilities essential for global operations. some text
    • For example, users of Interu could view a translated version of a foreign-language document they see in front of them with just the click of a button, and store it alongside the original.
  • Document Classification and Management: AI excels in classifying various document types, such as invoices or logs, which are crucial in trade and commerce. AI can also suggest optimal ways to split large PDFs into individual documents, enhancing file management. some text
    • For example, users of Interu could upload a PDF containing a scan of multiple documents, and let AI suggest the start and end of each document contained, and identify its type.
  • Optical Character Recognition (OCR): AI's ability to interpret printed and handwritten text transforms data entry, making it faster and more accurate. This is particularly useful in processing forms and extracting crucial data. some text
    • For example, users of Interu could upload a scanned document and ask their AI co-pilot to automatically enter the data contained in it into Interu.
  • Advanced Data Handling: From extracting sender and recipient details to understanding line items on invoices, AI can parse complex document layouts and extract meaningful information, a task that is challenging even for seasoned professionals. some text
    • For example, a user of Interu could engage the AI co-pilot to automatically collect issuer and recipient information, as well as the document’s date, number,  all quantities and totals from an uploaded document.
  • Fraud Detection and Security: AI systems can perform plausibility checks and duplicate upload checks, adding a layer of security and integrity to transactions.some text
    • For example, for a user of Interu, AI could check for each uploaded document, whether a very similar version of this was already uploaded earlier, and flag the uploaded version for review.

The challenges and considerations

While the benefits are significant, the deployment of AI in traceability systems is not without its challenges. The quality of AI outputs can vary based on the data it has been trained on, necessitating continual learning and adaptation to specific business environments. 

Moreover, AI systems must be used responsibly, with a clear understanding that they support, rather than replace, human judgement. For example, the potential fines of non-EUDR compliance is up to 4% of a organisations annual EU revenue (which for some large enterprises can be as high as 3.9 billion euros) so the responsibility of conducting due diligence is still on the user. AI can not and should not replace that. 

Conclusion: AI as a strategic enabler

As AI continues to evolve, its role in enhancing the capabilities of enterprises across industries will only grow, underscoring the need for businesses to adopt and adapt to these technologies thoughtfully and strategically. However, at iov42 we believe that any AI implementation should be approached with careful testing and consideration of its impact on existing workflows. 

Interested in being part of our beta testing? Then get in touch!

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