In today’s economy, information overload is fast becoming the norm. From sifting through flooded inboxes to endless scrolls on LinkedIn, there’s a continuous stream of new information constantly headed our way. With everything competing for our attention, it’s making it increasingly difficult to focus on what truly matters.
This also has a profound impact on how we ideate and innovate. The rise of AI, especially Generative AI (GenAI) has added to this complexity. With GenAI being the first technology that is now capable of creating and approximating more human-like ideas and combining concepts in novel ways, it is becoming more difficult to discern where human creativity begins and the influence of AI ends.
GenAI, however, is not here to replace human ingenuity or our unique problem-solving abilities. Instead, it prompts a bigger question: How is AI reshaping corporate innovation? What are the opportunities and drawbacks of this technology, and how can organizations position themselves to embrace an AI-driven future?
Seismic Shifts in Corporate Innovation
Innovation has always been a key discipline for organizations to stay relevant in a fast-changing world. While AI has been around for some time, the emergence of large language models (LLMs) like ChatGPT, have sparked concern amongst many businesses, with fears of industry disruption and job losses. While these concerns are partly justified, in the context of corporate innovation, GenAI simply represents another shift in a long history of change.
In the early 20th century, up until the 1980s, corporate innovation was primarily seen as a form of diversification, rather than as a separate strategic priority. Many executives relied on their personal experiences and intuition to drive company-wide innovation efforts. Towards the late 20th century, innovation became more integrated into the overarching business strategy, by companies establishing dedicated teams and departments leading corporate innovation efforts, formalizing the approach.
The 21st century saw a shift from closed innovation to open innovation models, welcoming the input of external parties and assistance through external ideas and technologies. Now, with GenAI, another shift is underway, which if harnessed effectively, can drive businesses to new heights.
AI as a Catalyst for Innovation
The possibilities of AI and GenAI to revolutionize traditional R&D processes as well as corporate innovation, are endless. If used in conjunction with an existing innovation management program, AI and GenAI can transform the innovation journey by accelerating and improving workflows, automating routine tasks, improving decision-making and act as co-pilot for coming up and validating new ideas. At rready, we’ve integrated AI into our innovation management software to help teams move more efficiently from ideation to implementation.
1. Identifying Problems
The first step in innovation is problem identification. Here, GenAI helps innovators as part of the brainstorming process by scanning through data sets and identifying certain trends in these data sets or recognizing possible market opportunities and gaps by analysing competitor activity. Unlike traditional machine learnings models, LLMs can understand and predict human behaviour in a way that is far more advanced than any other previous learning models, leading to more sophisticated outcomes, even as early as the problem identification process.
At rready, the combination of GenAI, our API-first innovation platform and proprietary company data unlocks new possibilities to uncover relevant problems and opportunities. We believe this will set a new standard for corporate innovation and fuel the disruption of innovation discipline as we know it.
Another useful way in which to incorporate GenAI in the innovation process, is by enabling innovators to discover ideas or solutions other innovators in their organization have come up with. Our rready platform features an advanced search function, which allows innovators to discover ideas from others, based on the similarities between ideas. This streamlines the innovation process, helping users avoid duplicating efforts on problems where solutions might already be in the works. We are also currently investigating how AI agents can help to do research and add up-to-date information on an idea level.
2. Creating and Enriching Ideas
Once an idea has been established, it is the task of the innovator to flesh it out. AI agents can analyse large data sets from the web or from internal proprietary company data sources much faster than humans and provide insights that enrich ideas with evidence-based reasoning. From customer preferences or user behaviour to market trends, or scientific research, GenAI helps innovators to synthesize complex information to support or refine their ideas further.
The ability of certain AI integrations to work cross-functionally also offers an opportunity, specifically when using innovation management platforms. The rready platform has AI-powered Dynamic Fields that react with AI integrations to help innovators not only create ideas or descriptions for these ideas, but also enrich these further through co-pilot support.
3. Rapid Prototyping and Simulation
Once an idea is validated, prototyping is essential. By creating a preliminary model, innovators can test, identify potential flaws and gather valuable feedback to iterate their solution. AI can speed up this traditionally time-intensive process, reducing costs and resources.
In product design for example, Generative Design (GD) uses AI-driven software to generate multiple solutions based on a given set of constraints, leading to faster and more efficient problem-solving. To create prototypes and simulations, the rready platform offers the use of AI connectors that facilitate an integration of AI into various tools and systems for challenges extending beyond the platform’s capabilities.
4. Implementation and Commercialisation
After developing a solution, GenAI can assist with market analysis and targeting strategies. By utilizing predictive analytics for example, companies can analyse historical and current trends to predict how a product or service would perform in the market. This allows organizations to adjust their marketing strategies in real-time, to allocate and use resources more efficiently.
5. Providing Oversight and Ensuring Continuous Improvement
AI plays a significant role in tracking and evaluating performance post-launch. For program- and innovation leads, AI helps maintain oversight and optimize programs by tracking key metrics such as KPIs or project ROI. For this, the rready platform offers AI-powered graph architecture to ensure a comprehensive understanding of relationships among ideas, people, and data.
The future of corporate innovation lies in the hands of top-level decision-makers in organizations and how they choose to integrate it. While incorporating AI into the innovation process can be daunting, the benefits are manyfold. Combining GenAI with innovation management tools, offers a comprehensive solution for streamlining and levelling up innovation across a company. This approach augments human creativity, while addressing the shortcomings of traditional human-driven processes, leading to improved product and service offerings.
