We are entering a new phase of global competition where technological leadership is increasingly synonymous with economic strength, industrial resilience, and geopolitical influence. Innovation is no longer just a corporate asset; it has become a central pillar of global strategy.

The United States, Europe, China, and other nations are investing aggressively in artificial intelligence, semiconductors, and advanced manufacturing. Governments are expanding industrial policy, and companies are under pressure to accelerate R&D, safeguard intellectual property earlier, and move from idea to impact with greater speed and confidence.

Global R&D investment has nearly tripled since 2000, reaching $2.75 trillion in 2023 (source: WIPO). Patent filings have surged in parallel: 3.55 million applications were submitted in 2023, with China alone accounting for over 1.58 million (source: WIPO). This is more than a volume trend—it reflects a shift in how innovation is being used as both an economic and geopolitical lever.

Companies Must Innovate Faster to Stay Competitive

This competitive landscape is reshaping how innovation creates value. Compressed development cycles enable faster learning, earlier IP protection, and quicker responses to market shifts. In high-stakes sectors like biotech, automotive, and electronics, first movers are capturing outsized value.

Firms that fall behind risk more than just market share — they may lose influence in supply chains, see their IP positions erode, and struggle to keep pace with more agile competitors.

In today’s global race, time is the new competitive moat. Companies that accelerate R&D and IP timelines are building structural advantages that will be increasingly difficult to overcome.

AI Is Transforming R&D and IP Workflows

Artificial intelligence is already reshaping how innovation gets done. Tasks that once took days or weeks—technical literature reviews, patent drafting, prior art analysis—can now be executed faster and more effectively with AI tools.

A recent Prosper Insights & Analytics survey found that over 43 percent of AI users rely on it for research. In pharmaceuticals, AI is reducing drug discovery and manufacturing product development timelines from years to months. A Financial Times analysis shows that AI and machine learning are enabling R&D to bring drugs to market up to four years faster, potentially adding $2 billion per successful drug and reducing costs by up to 45%. Faster innovation is not just efficient—it’s strategically transformative.

At Ankar, we've seen this firsthand with several of our customers. These companies show how applying AI strategically to their IP operations has led to measurable gains in speed, quality, and control:

Example 1: One of Europe’s largest consumer brands is facing a growing backlog of invention disclosures and bottlenecks in their freedom-to-operate checks. Within a month of deploying Ankar’s Launchpad with their legal team, they were able to file 50% more patents while cutting their backlog in half. Launchpad accelerated prior art discovery, highlighted core inventive claims, and automated formatting, enabling attorneys to focus on strategic claims.

Example 2: A major global automotive supplier was experiencing slow drafting cycles that impeded its ability to file patents and manage a rapidly expanding innovation portfolio. With Ankar’s AI solutions, the company accelerated key steps in the patent drafting process, significantly speeding up filings while maintaining oversight and quality. By leveraging AI assistants to generate and edit patent specifications, the team can now more of their time on high value-adding activities.

Example 3: The IP and R&D team of a global pharmaceuticals company faced challenges navigating the complex patent landscape and identifying promising R&D opportunities. Traditionally, this required manually reviewing hundreds of patents—an inefficient and error-prone process. With Ankar, they were able to rapidly locate and assess relevant patents with far greater precision. By streamlining freedom-to-operate assessments and competitive analysis, the team reclaimed time for deeper strategic work and more confident decision-making.

Companies and Regions Embracing AI Are Pulling Ahead

A widening gap is emerging in how AI is used to transform R&D and IP workflows. Globally, companies that adopt AI are filing faster, scaling knowledge, and freeing up time for high-value work—becoming more resilient, adaptive, and competitive.

Across Europe, many firms still face slow, manual processes and fragmented workflows. This isn’t simply a funding question; structural factors—regulation, bureaucracy, and ecosystem maturity—play a role. As Nobel Laureate Jean Tirole has noted, “The EU is losing the race for innovation.”

Yet this is also a moment of opportunity. European companies that modernize early can differentiate themselves, attract top talent, and even leapfrog competitors. By aligning leadership, reallocating resources, and adopting AI tools that turn friction into velocity, firms can turn structural challenges into sources of competitive advantage.

The real risk is not that Europe lacks talent, capital, or ambition—it’s that too much of this potential is locked inside outdated systems and processes. AI adoption is not about chasing hype; it’s about enabling scientists, engineers, and IP professionals to work at the pace required in a global innovation race. Those who make this shift will not just keep up with global leaders—they will help define the next wave of European competitiveness.

Conclusion: A Pressing Need to Accelerate R&D

The global economy is reorganizing around technological power. In this environment, innovation speed is no longer just a metric, it’s a measure of strategic strength. Companies that adopt AI-driven R&D workflows will lead in product development, resilience, and market influence. Those that delay will face slower cycles, higher costs, and growing irrelevance.

The practical step forward is clear: identify where innovation gets stuck and remove those frictions. AI applied with purpose, especially in high-friction expertise-heavy processes, enables step-change improvements in speed, consistency, and clarity.

We’ve seen this shift firsthand. From accelerating patentability analyses to enhancing patent drafting, companies using AI aren’t merely keeping pace—they’re setting it.