Business leaders and managers face increasing pressure to make the right decisions in the workplace. As a result, AI for business leaders is an important aspect to help in decision making and problem solving. More and more business leaders are turning to AI powered technologies to help close the data-insight gap and improve their decision-making capabilities in time-critical, high pressure situations.
The artificial intelligence technologies in businesses help encompass a wide range of tools. These include virtual assistants, virtual and augmented reality, tools for process discovery and task mining, and an array of data analytics and business intelligence platforms.
Well-known generative AI models include OpenAI’s ChatGPT, Google’s Bard, Meta’s Llama 2, and Anthropic, but there are many more.
Critical questions faced by decision–makers
The critical questions faced by decision-makers in using AI for decision making and businesses are
- How is AI going to be helpful in decision making?
- What are some of the challenges and risks of using AI tools for business?
- How are AI tool effectively beneficial for business leaders while mitigating the risks?
How AI improves decision making for business leaders
AI-powered technologies can drive faster and better decision making in at least three main ways: real-time tracking and improved prediction of on-the-ground business developments, virtual role-play to train workers in life-like business scenarios, and emerging generative AI tools that can answer questions and act as advisors and virtual “sounding boards” for decision makers.
Helps improving supply chains
With increasingly fine-grained data coming from technological tracking of supply chains, firms can now understand where their raw materials and inputs come from, who produced or supplied them, and whether these inputs have been produced and sourced in an environmentally friendly and ethical way.
Seaports are also turning to AI-enabled technologies to orchestrate and streamline decisions, improve operational performance, and ameliorate environmental impacts. The margin for error is small, and AI can help keep errors at bay.
Virtual in real-world conditions
Many industries now deploy AI-powered technologies to equip workers and managers with decision-making skills in both the routine and the unexpected situations.
Applications of VR can be used to train people in decision-making, from policing to health care to engineering design to utility infrastructure maintenance.
AI a virtual sounding boards
AI for business leaders is also playing an important role in decision-making as virtual advisors and sounding boards. In principle, generative AI systems can help overcome some of the problems affecting human decision making. Specially when it comes to making decisions under pressure. Generative AI tools can potentially help decision makers save time, conserve energy, and free up time to focus on the issues or questions that matter most.
Future of AI as co-pilot
An emerging application of generative AI is the development of decision “co-pilots” that can assess information in dynamic situations, suggest options and next-best steps, and complete tasks.
One of the biggest potential applications of generative AI is in the checking and testing of ideas, providing a kind of virtual sounding board.
In fact, the “creative side” of generative AI is likely to become even more important to decision makers in many different fields and industries in the future.
Imperatives of AI for business leaders
While AI systems are being used increasingly to support, and in some instances supersede, human decision-making, challenges and risks abound. These risks include issues of potential bias, ethics violations, data-provenance concerns, and accuracy, to name but a few. They also raise some pointed questions for businesses investing in such technology. As a decision maker, when do you trust the machine over the human? What are the conditions for effective human-machine collaboration? How does existing human expertise and judgement enter the equation?
Our research and experience suggest four imperatives for business leaders:
Be domain-specific
While generative AI models can in principle be applied to a vast range of decision-making situations, they are likely to be much more effective when applied to discrete problems using well-defined organizational or market data.
Pay attention to the experience curve
Research indicates that the skills and experience profiles of workers whether they are experts or novices, or somewhere in between makes a big difference in how they interact with AI technology and the expected impacts. Skill levels, experience, organizational knowledge, and proficiency with technology are all factors that business leaders will need to carefully calibrate in designing AI skills strategies and applications.
Maintain expertise currency
While organizations may be tempted to see generative AI as a short-term route to automation and cost savings, the longer-term risks of worker and organizational deskilling are real.
Prompt engineering
Generative AI is giving rise to a new discipline called “prompt engineering” — in essence, how to structure questions and prompts to AI systems to get the best possible answers. Business leaders and managers today have more data, coming from more sources, than ever before. Paradoxically, however, the data deluge has only intensified the pressures on executives to get critical decisions right. AI tools can lighten the cognitive load and improve decision-making effectiveness in many ways: improved tracking and simulation, realistic practice in virtual settings, and real-time AI-powered decision advice. But, to realize these benefits, organizations must approach human-machine collaboration with their eyes open, paying attention to the strengths, weaknesses, and limitations of AI systems. Most importantly, human decision makers must continue to develop their own skills, expertise and judgement, so that they can use AI in the right way while mitigating the risks.
AI presents both immense potential and significant challenges. While it promises greater efficiency, innovation, precision, and personalized experiences, it also poses many unknowns and underscores the need for careful and thoughtful implementation. Leaders must navigate these transformative times with an open and rational mind. Therefore, it’s crucial to continually evolve and refine own perspectives, ensuring that while we work to harness AI’s capabilities, we understand its implications and prioritize the fundamental essence of human contribution and human values.
