Finding the right artificial intelligence partner for your R&D team is just like interviewing a job candidate. You want to know about their background, experience, and expertise. You’re also interested in whether or not you can work alongside them and if they’re worth their desired salary. Selecting an AI-backed innovation discovery tool that fits your existing team also requires thorough research. These five questions can help you choose the right tool for your unique needs.
1. Does it have comprehensive coverage?
You need to know if your innovation discovery tool’s database includes all of the literature your organization needs to make data-backed decisions. Both quantity and quality are essential. Whether you’re performing prior art searches, patent landscape studies, or freedom to operate evaluations, your research should include as much relevant information as possible. Your innovation discovery tool’s coverage should include not only your core technologies but also parent technologies and affiliated sciences.
Having access to a lot of content isn’t enough; the sources must be credible as well. High-quality databases include up-to-date publications from government agencies and industry leaders worldwide.
2. Can it excel in your industry?
You expect a job candidate to have an understanding of your industry. Likewise, AI can be a huge asset to your discovery process, but only with the proper training. AI trained on data in your field is essential to its success. For science and technology R&D, an innovation discovery tool trained on scientific and technical publications will likely provide the most benefit.
3. What special skills does it offer?
AI excels at detail-oriented, time-sensitive tasks, allowing humans to take on more complex parts of the innovation process. Your AI innovation discovery tool should allow researchers and engineers to find and analyze relevant literature more quickly.
The right tool not only returns search results; it will also offer a variety of perspectives from which to view and interpret those results. Value-added capabilities include visualization, mapping, valuation, and automation. This symbiotic relationship between AI and humans leads to unexpected answers and actionable insights.
4. Can you work together?
The potential benefits derived from AI are only possible if it’s intuitive. Your team will likely find an innovation discovery tool well-versed in Natural Language Processing (NLP) to be the easiest to use. When your innovation discovery tool is powered by machine learning trained in your specific field, your semantic search results will be more relevant and valuable. For even more powerful searches, combine Boolean operators with your natural language entry.
The most helpful AI team members offer a user-friendly interface with the ability to save, share, and export your search results.
5. Is it worth the money?
Consider the inherent strengths of an AI innovation discovery tool, such as faster searches and thorough results. Then, ask yourself if you can afford to operate without the power of AI on your team. The right tool can both minimize operational costs and maximize the potential of your intellectual property. Using AI for innovation discovery allows organizations to:
- Gather competitive intelligence
- Prioritize research investments
- Create stronger patent applications
- Bring innovations to market faster
- Develop IP monetization strategies
- Manage patent portfolios
- Determine litigation strategies