As we all know by now, the pace of innovation and change in the times we live in is staggering and this doesn’t seem to slow down any time soon. Just so far this year, we are seeing examples of how virtual and augmented reality is now becoming mainstream in the form of Apple Vision goggles, BCI’s (brain-computer interfaces) are connecting the human brain with computers through implants from Neuralink and NLP and LLM (large language models) capabilities keep advancing every week, with video generation being the latest jaw dropper from Open AI). And, surely, if you read these scribbles some time, or even weeks, after they were put on paper in March 2024, these things will seem like old news and they will have been replaced with even more mind blowing inventions.

So, with all of these advancements, can we afford to keep doing things the same way we have done them before? In some cases the answer to this is “yes”, and maybe even “yes, we have to”. But in most situations, the reality is that we have to start looking at utilizing new technology to keep up and enhance our lives, our professions, and the product of our work.

As it relates to Artificial Intelligence, which will continue to be one of the hottest topics, and as we are in the business of advancing the patent information space, I wanted to share some of my realizations and thoughts about why this is a great time to consider making a change of patent search, monitoring and classification tools. Continuing throughout this year may likely mean losing too much ground.

1. Macro- and microeconomic realities

The last few years have been tough in many ways, with a recession and businesses that have had to recalibrate and sometimes even scale back. Many of the people and functions we speak with simply don’t have the same resources to solve problems and produce the same or more/better results, while the need for what they produce keeps increasing. Hence, looking at ways to improve and enhance processes using modern tools to overcome these challenges is crucial, to avoid decreased efficiency and effectiveness.

2. Industry convergence and changed needs

For some time now, industries have consolidated and converged and the lines between technologies have blurred. This will continue, or even accelerate. With this in mind, do we still know and have the required skills to digest and understand all types of technology that we now have to research and analyze? We may know everything there is to know about one area, but is this enough? If we are unsure of the answer to these questions, what does this mean for a company’s or organization’s ability to manage risk or capture opportunity, and is there technology to assist available? The short answer to this last question is yes, there are, and they should be considered if these challenges are affecting the work we do.

3. Patent quality and the patent system

The patent system is fundamentally important for promoting and protecting many of the technological and scientific advances we see, and many of these would likely be impossible without it. But, the way this system is being administered is being challenged, and the administrators of this face the same challenges everyone else is facing, in high volumes and more complex domains. Hence, some may be questioning whether how things are being administered allows for high quality patents, in a time when things like quality, predictability and certainty are more important than ever. I have no opinion on this per se, but it’s clear that technology, and artificial intelligence, will be crucial to sort the problem out, both for the administrative bodies and for the companies that depend on patents to protect their business and invest in protecting their inventions.

4. Maturity, AI initiatives and adoption

While this wasn’t the case just a year or two ago, most organizations have specific budgets and working groups allocated to AI assessment and adoption now. We can see, in conversations with our customers, that there is a more sober and mature way of looking at these things, and that most organizations see that the benefits of Artificial Intelligence are obvious. Hence, there seems to be both external and internal momentum. Given that the legal, and in particular IP, space is one of the areas that can benefit the most from adopting AI and automation, these initiatives and new ways of looking at the possibilities should also have a positive impact on creating positive change in our space. The timing is perfect, and for once we seem to have resources allocated to drive change proactively. So if e.g. patent research and analysis are not part of these discussions and initiatives, they should be, and it’s up to us to ensure that they are. There is, literally, no time like the present!

5. Security and risks

Closely linked to the maturity mentioned above, we should also acknowledge that the security aspects remain top of mind and very important, but that the risks are clearer and easier to control for companies. When we know which boxes need to be checked from a security perspective, it’s easier to focus on the positives. We see a lot of focus on this when we speak with our clients, but most companies now know what to ask for, and a lot of investment has also gone into ensuring that the tools and services can be delivered safely and securely (for example, here’s our approach). So, we’re moving back towards focusing on what the tools can do, instead of how they do it and the potential risks associated with adopting AI tools, which, compared to just last year, makes this time ideal for assessing new opportunities.

6. Last but not least – Capabilities

If the AI and automation solutions we’re talking about here are not significantly improving processes and capabilities, everything else is irrelevant. Luckily, the leaps forward these past few years have made it clear that they are. AI can and will help. In our space, where AI and new technology have always been compared to traditional methods and efforts, we can now confidently conclude that quality, reliability, speed and security is there (more so in some solutions than others, but generally speaking, this is the case). E.g. AI can now, in many situations, find prior art with similar or better accuracy and substantially faster than previously possible. In addition to this, many of the software providers (including, of course, IPRally) are starting to develop capabilities that go beyond just one or a few use cases, and the ecosystem we all operate in is starting to see less “one trick ponies” which makes it easier to implement fewer and better solutions (see some more thoughts about other processes and use cases that are improved here).

Conclusion

Considering the macro environment in combination with the increased maturity and security of AI initiatives, there is too much to gain from adopting new technologies and replacing the old to not do it this year. 

Let us know your thoughts, and how we can help. Do you agree or disagree?

Finally, the process of writing this down took me to a fairly abstract place, where big macro trends dominated the list. This makes sense from one angle but becomes more relevant when taken down to things that impact our day to day. Hence, look out for part two of this blog where I will share my thoughts about the state of patent research and classification tools in general, and some of the things that will have a direct impact on you as a user or beneficiary of such tools.

Continued in RallyCast

This blog post is discussed in the second episode of RallyCast.

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