Bob Bress, Vice President and Head of Data Science, FreeWheel
introduce
The rapid development of artificial intelligence (AI) is not only a technological revolution, but also a paradigm shift in the way enterprises operate.For CIOs, data leaders and decision makers[1]For manufacturers, the challenge is no longer just adopting AI, but structurally adapting to its ever-accelerating pace. The question is not just how we use AI to drive operational efficiencies and product enhancements in the coming months, but also how we set up our companies to quickly adapt as new capabilities emerge in the coming years. To lead this era of technological advancement, companies need to create structures and frameworks that enable rapid innovation in an increasingly competitive global economy.
The impact of dynamic artificial intelligence landscape on team structure
As new AI capabilities reshape how industries operate, traditional team structures need to be reimagined to quickly adapt as new technology breaks through. Artificial intelligence will move beyond the automation of routine tasks and begin to master higher-order skills such as software development. Business skills involving creativity, strategic thinking and execution agility will become even more valuable. The level of basic knowledge of all employees using AI systems will increase as they are critical to increasing productivity. AI experts need to work alongside domain experts to identify new ideas that leverage the latest AI capabilities. Project teams must be more agile in bringing together the right skills to innovate quickly. Overall, building teams to leverage AI-based technologies will need to be a strategic priority.
Key Strategies for Building an Artificial Intelligence Development Team
1. Cultivate a culture of continuous learning:
The AI tools available in 12 months will be very different from those available today. Companies need to build and foster a culture of continuous learning, especially around AI research and tools. This can include training courses, seminars or other educational opportunities to enable employees to stay on the cutting edge of new technological developments. As AI capabilities advance, continuous learning needs to become an expectation among employees to maintain a company’s competitiveness.
2. Celebrate experiments:
The innovation that drives company performance will come from a culture of testing and learning.Companies need to promote experimental spirit through activities such as hacking[1]Marathons or innovation days where employees have time to explore new ideas.These concepts need to be expanded to ensure innovative thinking is realized this year[1]round. Successful cultures value failed experiments as steps toward greater breakthroughs.
“Building an artificial intelligence development team is not just about gathering talent, but about creating an ecosystem of continuous learning, collaboration, and innovation.”
3. Build with cross-collaboration and team diversity in mind:
The broad applicability of artificial intelligence and its potential to impact every aspect of the enterprise require diverse perspectives to drive innovation. Diversity in the makeup of an AI team is critical. This is not just about gender or race, but also about different academic backgrounds and ways of thinking. Leading AI development teams at companies like Microsoft, IBM, and Google are known for bringing together engineers, analysts, sociologists, and strategists to collaborate on new AI development initiatives. This provides a comprehensive approach to problem solving. Just as AI models trained on specific subsets of data are prone to bias, so are teams with limited diversity of backgrounds and expertise.
4. Agile product development, move quickly
Artificial intelligence projects benefit from agile methods. Accelerating AI innovation means significant changes in the field in the long term. This means short development cycles, regular feedback, and adaptability are valuable in leveraging artificial intelligence to consistently deliver real business impact. Small cross-functional teams working autonomously on different aspects of the product will enable the company to move quickly.
5. Invest in AI leadership:
Company leadership needs to be well-versed in how AI can benefit their company, industry, and customer base. Every leader should have clear goals regarding how to use artificial intelligence to move their team and company forward. These leaders should understand the strategic and ethical implications of AI and guide their companies through AI integration. As AI becomes a key component of company growth, more specific leadership roles will emerge in the AI field.
Building an artificial intelligence development team is not only about gathering talents, but also about creating an ecosystem of continuous learning, collaboration and innovation. Our approach to team building needs to be strategically built to move quickly and adapt to new capabilities, positioning our teams to assume the role of leading industry innovators and bringing new value to our industry. Now is the time to reflect on whether we are ready to accelerate the development of artificial intelligence and take the necessary steps to lead the way.
