The Power of Collaborative AI

We may have to go a long way back in history, perhaps maybe even back to the times that nuclear technology was being harnessed to find a parallel of a time when a new technology has caused extreme reactions artificial intelligence (AI) has had. From Elon Musk’s warning that it can cause civilization destruction to Geoffrey Hinton, often referred to as the Godfather of AI, who echoed similar thoughts that unexpectedly rapid advances in AI—including its ability to learn simple reasoning—are a suggestion that it could someday take over the world and push humanity toward extinction. Even lawmakers are still debating about what to do or how to regulate this new capability that technology has just served.

There are, of course, endless forms in which AI can be deployed—from fully autonomous forms to multiple, narrow hybrid AI applications where AI systems are deployed to complement and compensate for the inherent constraints of human cognition to make the collective (human and AI) systems and teams more effective.

In this hybrid format, there are numerous advantages to harnessing the potential of AI, given that we will always be a world of infinite needs and aspirations but always of finite resources. Any technology that can help stretch our abilities and resources can help us not just in meeting a larger part of our infinite needs but also in eradicating numerous challenges civilizations have tried to address for generations.

Enter “collaborative AI,” a format that is human-centric and AI as a supportive tool or member of a team with a promise to transform numerous industries and businesses.

For supply chains, adopting AI models can have benefits across various functions from launching new products, and optimizing inventory to fulfillment and beyond. For our present conversation let’s explore AI’s potential to revolutionize the way new products are created within the supply chain and where AI can transform this important function.

Improved market research and consumer insights

AI is revolutionizing market research and consumer insights, providing valuable data and analysis to inform product creation. AI algorithms can analyze vast amounts of consumer data, including social media trends, online reviews, and purchasing behavior. This allows companies to gain deeper insights into customer preferences, demands, and emerging and waning trends.

With a dynamic, deeper, and multi-dimensional understanding of consumer needs and preferences, companies can develop products that are tailored to meet the needs and expectations of their target market, increasing the likelihood of success without wasting time and resources in trial and error or prototyping multiple options. This gives an unparalleled ability to serve micro markets which hereto could not be served profitably by companies given the high cost of understanding deeply the needs of these customers.

These new insights can have a transformative impact on industries like fashion and retail where multiple new products are constantly launched or where speed to market with a new trend or product is a large competitive advantage.

Efficient ideation and concept generation

When it comes to the creation of new ideas or the genesis of new concepts, we view it through a lens of our feelings, emotions, experiences, beliefs, and biases. These serve us well in many ways and help guide our decisions and have always had a significant role to play. The process of ideation and concept generation can be significantly enhanced through AI technologies. AI-powered systems can analyze vast databases of historical data, patents, and market trends to generate new product ideas based on emerging trends.

Machine learning algorithms in AI systems can identify patterns, detect market gaps, and propose innovative concepts. AI tools can also help analyze competitor pricing and customer price elasticity to propose ideal selling prices for new products that maximize the profitability and success probability of the new products. This expedites the ideation process and allows companies to explore a broader range of possibilities for new products, fostering creativity and innovation.

Accelerating design and prototyping

AI can accelerate the design and prototyping phases of product creation within supply chains. AI-powered design tools can assist in generating and refining product designs based on user requirements, market trends, and manufacturing constraints. By leveraging AI algorithms, companies can automate design iterations, saving time and costs. Additionally, AI can simulate and optimize product performance, ensuring that the design meets quality standards and customer expectations. Rapid prototyping technologies, such as 3D printing, can be integrated with AI systems, enabling quick and cost-effective prototyping iterations.

Streamlining supply chain collaboration

One may ask, how can a nameless, faceless AI program improve collaborations?

Actually, AI can facilitate seamless collaboration and communication in the supply chain, an area with endless opportunities for improvement. AI-powered platforms and tools enable real-time sharing of information, documents, and feedback across different stakeholders involved in the product development process and can assimilate comments, feedback and ideas without bias into workable go-forward proposals. This fosters effective collaboration between designers, engineers, suppliers, and manufacturers, reducing delays and miscommunications. By streamlining collaboration, companies can accelerate decision-making, identify, and resolve issues promptly, and ensure a smooth flow of information throughout the product creation journey. Most importantly for teams, the removal of personal bias in this process can bring forth cultural wins where everyone has had an equal opportunity to contribute and there is a pure idea of meritocracy.

Correct inputs at the correct time

The three biggest showstoppers of progressing with new product innovations in any company are usually finding out that a prototype cannot be replicated in bulk or that someone, somewhere, has done it before and has a copyright or patent on it, or that the final cost will be beyond the acceptable range. Most teams would then go back to the drawing board after having spent a large amount of time and sunk costs to get to this stage.

Leveraging AI, assimilation of this universe of downstream information and input is available during ideation and creative processes which can pre-qualify all go-forward ideas, saving costs and improving speed to new products to market magnifying the potential of the creative teams.

Predictive analytics for demand forecasting

AI’s predictive analytics capabilities can revolutionize demand forecasting within supply chains. By analyzing historical sales data, market trends, and external factors, AI algorithms can generate accurate demand forecasts for new products. This allows companies to optimize production planning, inventory management, and supply chain operations. By aligning supply with anticipated demand, companies can minimize stockouts, reduce excess inventory, and enhance customer satisfaction. AI-powered demand forecasting provides valuable insights for decision-makers, enabling them to make data-driven choices regarding production volumes, sourcing, and distribution.

Quality control and product testing

AI technologies play a vital role in improving quality control and product testing in supply chains. AI-powered systems can analyze large volumes of data from various sources, including customer feedback, sensor data, and manufacturing parameters. This data analysis allows companies to identify potential quality issues, detect anomalies, and ensure that products meet the required standards. AI-powered inspection systems can automate quality control processes, reducing human error and enhancing efficiency. Additionally, AI can simulate product testing scenarios, enabling companies to predict and optimize product performance and durability.

Conclusion

The emergence of AI brings immense potential for transforming the way new products are created within supply chains. By harnessing AI’s capabilities, companies can enhance market research, accelerate ideation and design, streamline collaboration, optimize demand forecasting, and improve quality control. These advancements lead to increased efficiency, reduced time to market, and enhanced customer satisfaction.

However, it is crucial to note that collaborative AI is not meant to replace human creativity and expertise. Instead, it augments human capabilities, enabling professionals to make more informed decisions and focus on higher-level tasks. The integration of AI into product creation within supply chains represents a significant opportunity for companies to drive innovation, stay competitive, and deliver superior products in an ever-evolving marketplace.

About the author:

Roit Kathiala has held executive roles in leading retailers across Europe, Asia and North America and consults and is the architect and advisor to leading companies on their business, digital, supply chain and product strategies.