AI: Think globally, act locally
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The state of productivity has been hotly debated for decades, with uncertainty surrounding the ability of information technology to boost output and GDP.
In my last post, I explained the complex relationship between technology and productivity on a global level.
Of course, business leaders and managers need to worry less about increasing global productivity and more about improving productivity at the “local” level. That means using the best people and tools available to keep your organization on a growth path. .
A new report from Deloitte suggests there are a number of strategies, including artificial intelligence and talent development, that can help individual companies increase productivity.
The study’s authors looked at 100 leaders’ approaches to improving productivity over the next 12 months. The study included private companies with annual revenues ranging from $100 million to more than $1 billion.
Participating executives say market competition (46%) and overcoming the limitations of legacy technology (44%) are major or very major barriers to improving productivity. Further he says 31% have limited access to capital investment.
Respondents from small organizations say productivity improvements are most needed in procurement, product development, and sales/marketing to achieve business priorities. Large organizations cited emerging technology, talent hiring, and human resources.
The good news, the Deloitte authors conclude, is that while AI is still in its experimental stages, it holds promise in many of these areas. Less than 10% of respondents said AI currently improves their productivity, but the majority (87%) expect it to improve within three years.
The study found that AI contributes most to productivity by shortening product manufacturing cycles and service delivery times, along with employee learning and development. Areas where AI is expected to improve include:
- Reduce product manufacturing cycle/service time by 40%
- Employee learning and development 39%
- Improved customer experience 34%
- Improve internal collaboration and communication 31%
- Optimize resource allocation 31%
- Automate 30% of repetitive tasks
- 30% faster and more accurate data analysis
- Optimize scheduling and time management 27%
- Enhanced problem solving 23%
Once planned, tested, and operationally deployed, AI has the potential to improve productivity more quickly than previous waves of technology. “While it took decades to realize the full potential of other technologies (electricity, the steam engine, the internet), the impact of generative AI on economy-wide performance and competition will become apparent in just a few years. According to an article from Harvard Business Review, by Andrew McAfee, Daniel Locke, and Erik Brynjolfsson.
AI’s productivity promise stems from the fact that AI is software-based, saving on the Nvidia chips needed for many of AI’s functions. “General-purpose technologies of the past required large amounts of complementary physical infrastructure (power lines, new types of motors and equipment, redesigned factories, etc.), along with new skills and business processes,” McAfee and colleagues said. says a colleague. Authors. “That is not the case with generative AI.”
AI is a technology that improves itself through learning, as evidenced by a study of 1,500 customer service agents at major technology companies, McAfee and his co-authors said. For example, this study found that the least skilled agents benefited the most from AI, and the learning of more skilled agents was incorporated into the AI system. ”
Overall, the study showed that: The number of chats that a single agent can handle has increased by almost 15%. Among new agents, the number of chats supported increased by her 35%. “Given the potential for generative AI to improve productivity in many functions (indeed, any function that involves cognitive tasks), calling it revolutionary is an exaggeration,” McAfee and his co-authors wrote. Not,” he added.
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