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Choosing the Ideal AI-Powered Technologies for Industrial Companies

The influence of artificial intelligence (AI) on all sectors is undeniable. Industries widely recognised for their digital focus such as SaaS, fintech, healthtech, and travel are leaders in this AI-enhanced revolution. But they're not alone. Traditionally heavy industries are also ripe for meaningful disruption through AI applications.

The Impact of AI on All Industries: A Closer Look

The influence of artificial intelligence (AI) on all sectors is undeniable. Industries widely recognised for their digital focus such as SaaS, fintech, healthtech, and travel are leaders in this AI-enhanced revolution. But they’re not alone. Traditionally heavy industries are also ripe for meaningful disruption through AI applications.

Companies have increasingly embraced automation and data-driven decision-making, shaping their approach based on their needs and capabilities. In this piece, we will outline the varied strategies companies can adopt to integrate AI into their business processes, discussing the strengths and weaknesses I’ve observed.

Establishing an Internal R&D Department: A Closer Look

A strategy that some companies adopt involves establishing an internal R&D department for AI technology development. Tech giant Siemens is an excellent example of this with its AI Lab leading the way in possible industrial AI applications.

Though Siemens has found success through internal research and development — such as reducing production times without hardware upgrades — most firms find the benefits of an internal department to be limited.

In the corporate world, slow processing times, low tolerance for errors, and high expectations can hinder potential projects before they reach their full potential. Startups, on the other hand, are agile and possess the crucial ability to pivot when necessary. Thus, it’s beneficial for companies following this approach to give their R&D departments a level of autonomy, akin to a startup, so innovation isn’t stifled by corporate rigidity.

Moving Towards Corporate Venture Funds (CVFs) or AI-Targeted Accelerators

In addition to Siemens, industry titans such as Toyota — through the Toyota Research Institute and later through Toyota Ventures — and Qualcomm, via Qualcomm Ventures, have invested heavily in promising startups specializing in AI, robotics, and other frontier technologies.

Firms like Fujitsu, through the Fujitsu Engineering Accelerator, and Volkswagen, which partnered with renowned Silicon Valley accelerator Plug and Play, are venturing into proprietary acceleration programs tailored to the demands and challenges of their industry sectors. By piloting projects with startups, and using their resources to aid these startups, the benefits are significant.

However, this approach also presents difficulties. The entrenched corporate culture often resists efforts to establish a venture fund or accelerator. Additionally, the operation of these funds is often restricted by protocols and rules set by the parent company. Traditional corporate processes may clash with the requirements necessary to develop revolutionary AI technologies.

The Importance of a Chief Digital Officer (CDO)

This method involves hiring a dedicated individual or forming a separate department committed to the company’s digitization. The Chief Digital Officer (CDO) will focus on forming AI adoption strategies and liaising with startups. Their mandate will include improving efficiency, competitiveness, and growth through digitization.

Potential downsides to this in-house approach include the potential discord in communication protocols between startups and corporate employees, and limitations related to the CDO’s existing professional connections for future partnerships. In addition, the CDO and the company’s overarching vision must align to prevent projects from stalling.

This model performs best in a corporation interacting with an outside venture capital fund. A venture capitalist can quickly recognize which of their portfolio companies could solve a specific need or problem.

The Power of AI-Themed Hackathons

Regularly held hackathons have shown to be potent tools for generating fresh and innovative ideas. Valuable products are birthed from these events, such as an AI-powered solution to optimize energy management systems, developed at a Schneider Electric event or an AI app that boosts wind turbine efficiency thanks to a GE-hosted hackathon. Companies like Bosch also have AI-centered events like their “Connected Experience” hackathon that focuses on AI and IoT innovations (source).

Success in organizing meaningful hackathons extends beyond the willingness to invest time and money. More importantly, it lies in understanding why you are doing it and how to utilize the results – the ideas generated by the participants.

Conclusion

While these four strategies could potentially pave the way for firms to amalgamate AI technologies into their processes and improve results, a common theme emerges: the critical importance of communication and understanding between two vastly different modes of working.

AI startups and innovators may find it a challenge to communicate with corporate employees. Improving this skill will be key, as reshaping today’s industries with the power of AI will require successful collaboration in the face of differences. Corporations should employ someone capable of bridging this communication gap. Google, for example, has an employee in place to teach startups how to find common ground with large conglomerates.

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