The advent of the internet era provides a compelling study of how companies’ responses to technological change can determine their success or failure. While it can be an admittedly tired comparison when doing the whole “a tale of two cities” thing, consider the contrasting stories of Blockbuster and Netflix. After all, there is a lesson in it for the AI-minded, which we’ll get to in a moment.
Blockbuster, the once-dominant movie rental company, failed to recognize the potential of online streaming and digital rentals. Despite having the opportunity to purchase Netflix early on, Blockbuster remained committed to its brick-and-mortar rental model. The company did not invest in retraining its workforce or adapting its business model to the digital age. As a result, Blockbuster filed for bankruptcy in 2010 and is now a case study in failing to adapt to technological change.
In contrast, Netflix, which started as a mail-order DVD rental service, quickly recognized the potential of online streaming. The company not only invested in the technology but also focused on retraining its workforce and restructuring its business model to support this new direction. Today, Netflix is a global leader in online streaming, with a highly skilled workforce that continues to innovate in a rapidly changing technological landscape.
As we navigate the AI revolution, these lessons from history are more relevant than ever. The challenge lies not only in leveraging AI to drive value but also in ensuring that your workforce remains skilled, engaged, and empowered in the face of this transformative technology. This post will explore key strategies and considerations for preparing your workforce for an AI-enabled future, drawing on insights from industry studies and expert advice.
Evaluate AI Strategically
When considering high-potential AI applications tailored to your industry or business needs, it’s crucial to look at successful examples. For instance, the PwC 2022 AI Business Survey reveals that companies leading in AI adoption focus on three areas simultaneously: business transformation, enhanced decision-making, and modernized systems and processes.
These companies are advancing their AI usage holistically, achieving valuable business outcomes that not only produce a functioning AI model but also significant ROI. Therefore, the guiding principles that shape your AI strategy should include a comprehensive approach that integrates AI into various aspects of your business, from decision-making to operations.
Cultivate Collaboration & Communication
Two-way communication channels are vital for facilitating AI literacy and buy-in across teams. McKinsey’s article on effective change communication highlights the importance of clarity, consistency, and engagement. Leaders should clearly communicate the vision of human-AI collaboration, emphasizing AI’s role as a tool to enhance, not replace, human capabilities.
For instance, PwC’s survey found that companies with a holistic approach to AI are more likely to achieve substantial value from AI initiatives, improving productivity, decision-making, customer experience, and more. This success is often attributed to open communication and collaboration between AI specialists, analytics teams, software engineers, and data scientists.
Keep Humans in Roles that Require Cross-Domain Thinking
As AI takes over data-intensive tasks, human roles will need to adapt within a hybrid human-AI workforce. The PwC survey indicates that companies successful in AI implementation are focusing on positions that require judgment, emotional intelligence, ethics, cross-domain thinking, creativity, and strategy setting. This approach allows for innovation and ensures that final decisions, oversight, and control rest with humans. The implications for talent development and culture are significant, necessitating continuous learning and adaptability.
Implement Controls to Maintain Accountability
As AI usage scales, governance and controls need to evolve. The PwC survey suggests that successful companies are implementing rigorous approval structures, bias testing, and continuous auditing processes to validate AI system outputs and detect issues proactively. They also maintain diverse teams to oversee AI systems across the lifecycle, ensuring that multidisciplinary expertise can question blind spots. Both technical and non-technical safeguards are essential, including extensive documentation of AI system designs, training processes, and capabilities for transparency.
Upskill Employees Continuously
Capability building for AI should be integrated into your people development strategy. According to the PwC survey, successful companies are making learning resources available across teams to build an understanding of AI systems’ capabilities, limitations, and responsible usage. They also provide training on complementary skills like critical thinking, communication, collaboration, adaptability, and basic data/digital literacy. Reskilling support is offered to help employees transition as workflows evolve alongside AI, fostering growth mindsets. The agility of learning should keep pace with AI advancements, emphasizing short iterative learning sprints rather than one-off training.
The future is humans and AI working symbiotically. With proactive management, you can implement AI in a way that elevates your organization while keeping employees engaged, empowered, and valued. What other considerations are top of mind as you navigate this forward? I’d love to hear from you and continue the discussion. Shoot me an email, or leave me your feedback in the comments section below.
[Image source via Wikimedia Commons]