Making good decisions with AI

Artificial intelligence is rapidly transforming how business leaders make decisions, especially in high-pressure situations. Research shows that decision-makers are under increasing stress, facing a growing volume of critical choices. To cope, many are turning to AI-powered tools like virtual assistants, data analytics platforms, and generative AI models. Used well, these technologies can enhance decision-making. But leaders must know when they’re beneficial, what risks to watch for, and how to effectively integrate them.

The stakes are high. Only 7% of companies currently use AI extensively for strategic decisions, yet 75% of executives believe generative AI will be a key differentiator for success. Over 40% of CEOs are already using generative AI to inform their choices. Early adopters are seeing results — Ant Financial employs AI for loan approvals while Amazon attributes 35% of revenues to AI-driven recommendations. The message is clear: effectively weaving AI into decision-making will be critical for staying competitive.

However, the human-AI dynamic is complex. Even with identical AI inputs, human decision-makers often reach very different conclusions. Our individual decision-making styles, biases and values shape how we use AI insights. There are key aspects of “meaning-making” that only humans can provide, like assessing subjective value, establishing priority between values, and choosing to discard previous judgements. These uniquely human capabilities are essential for making AI truly useful — in research, product design, policy-making and more. Businesses must recognise where human wisdom is irreplaceable.

Trust will be a major factor in adoption. Globally, trust in AI varies hugely, from 75% of people in India to just 15% in the UK. Building confidence is key. AI must be transparent, not a “black box.” Users need control to adjust parameters. And crucially, AI has to actually perform — inaccurate or unfair models will destroy trust fast. Extensive testing, auditing and adjustment is required before high-stakes deployment.

A cautionary example comes from AI used in judicial decision-making. When an algorithm was applied to bail hearings, it actually performed worse than human judges at predicting re-offenders, leading to excessively harsh suggestions. Judges rejected the AI’s advice in over 30% of cases. While in theory the AI was transparent and adjustable, in practice it was not yet reliable enough to assist such weighty rulings. The researchers suggest more calibration could help, but clearly AI is not yet outperforming humans here.

So, what’s the takeaway for business leaders? Be strategic about where you leverage AI in decision-making. Look for places where AI’s rapid data analysis can shed light on complex, dynamic situations. Let AI highlight key patterns, calculate probabilities, or generate creative options. But keep humans firmly in the loop to apply judgment, consider ethics, and make final calls. Continuously monitor AI performance and impact. And invest heavily in building trust — in your AI tools and in your people’s ability to use them wisely.

The future is a human-AI collaboration, not competition. AI can be a powerful tool to enhance decision-making, but it is not a wholesale replacement for human leadership. By focusing AI on what it does best — swiftly processing vast information — we free up human cognition for what we do best: thinking critically, applying values, and crafting wise strategies. With the right approach, this potent partnership of artificial intelligence and human ingenuity may be the ultimate competitive advantage.

Consider these strategic insights:

• Pilot AI-assisted decision-making in low-risk areas first: Before deploying AI for high-stakes strategic decisions, test it out in lower-risk operational areas to build trust, refine processes, and demonstrate value.
• Upskill leaders in AI literacy and effective human-AI collaboration: Invest in training programs to help decision-makers understand AI capabilities, limitations, and best practices for leveraging insights while applying human judgment.
• Establish clear guidelines and oversight for AI use in decisions: Develop policies outlining when and how AI should inform choices, what human checks are required, and how to monitor for bias or errors.
• Proactively communicate AI use to build customer and stakeholder trust: Be transparent about where and how AI is assisting decisions that impact customers, employees, or the public, and provide clear avenues for feedback and recourse.

Signals from the future:

Emerging trends that are likely to drive changes to the way we live, work and do business.

• Why Gen Z are buying “dumbphones” to limit screen time — ZME Science — Generation Z is increasingly turning to “dumbphones” to reduce screen time and combat digital addiction, reflecting a cultural shift towards intentional technology use.
• 1X unveils NEO Beta as it prepares to deploy humanoids into home pilots — The Robot Report — Humanoid robot NEO Beta by 1X Technologies targets household tasks, prioritising safety and consumer feedback. Industry shift towards consumer robotics shows strong market potential.
• Record 99.9% qubit fidelity achieved by prototype quantum processor — Interesting Engineering — Breakthrough achievement in quantum computing with near-perfect qubit fidelity, paving the way for powerful applications in various industries and establishing leadership in the field.
• Solar will get too cheap to connect to the power grid. — Ben James — Solar panel costs are dropping, boosting solar power production which may strain power grids. Businesses face challenges with reduced profitability and grid connection delays.
• Natural gas demand drops by 7.4% to 12.72 TJ in 2023–502 Bad Gateway — Key Insight: European Union’s declining natural gas demand signals a shift away from Russian fossil fuels, impacting energy consumption patterns for businesses.
• Walt Disney Was Right; Our Cities’ Problems Are Our Biggest Problems — population.fyi — Successful Case Studies : Examples like Houston’s homelessness reduction and Akashi City’s population growth demonstrate that applying quality management principles can significantly improve urban areas, even in areas traditionally considered outside a city’s scope. Whether addressing homelessness, water conservation, promoting families, or creating liveable urban spaces, the common thread in successful initiatives is a commitment to effective feedback governance, careful (not total) use of metrics, and a willingness to invest in long-term solutions — things that affiliated with Total Quality Management.
• Electric Road Systems, towards decarbonising road transport — Futura-Mobility — Mobility and transports, innovation and research — Based on the fact that electricity is easy and cheap to transport but difficult to store, as for rail and metro systems since the early 20th century electric current could now be delivered on the roads.
• AI ‘won’t replace’ creative skills, study finds — ZDNet — Creativity is key for career success in the age of AI, but education must do more to foster this essential skill for the future workforce.
• The US Is Adding Grid-Scale Batteries at 10 Times the Pace of Natural Gas This Year — Singularity Hub — Rapid rise in grid-scale battery installations outpacing natural gas power capacity, highlighting shift towards renewable energy and need for energy storage solutions.
• UN 3D prints homes from mud in Colombia to fight housing crisis — Interesting Engineering — Revolutionary 3D-printed housing in Colombia offers cost-effective, sustainable solutions for affordable housing shortages, setting a new standard for global construction practices.
• Robots are coming to the kitchen − what that could mean for society and culture — Future(s) Studies — Robotic kitchens offer efficiency and creativity but may erode cooking skills, cultural diversity, and job opportunities while raising safety and ethical concerns for businesses.
• The Technology That ‘Could Turn The World Vegan’: Precision fermentation could help the world move away from animal agriculture — Future(s) Studies — Revolutionary precision fermentation technology offers sustainable, ethical alternatives to animal products, driving environmental benefits and market growth in the food industry.
• Google trains AI on 300M sounds to detect diseases via smartphone audio | Exploring bioacoustics, which combines biology and acoustics, demonstrates the growing use of AI to extract important information from human sounds. — r/Futurology — Harnessing AI and bioacoustics, Google’s HeAR model detects diseases from audio signals, advancing remote screening for tuberculosis in underserved regions.
• Revolutionary 3D Printing System Safely Assembles Living Organisms in Real-Time — Impact Lab — Revolutionary 3D printing system autonomously positions living organisms with precision, enhancing bioimaging and cryopreservation processes while paving the way for portable field applications.

Deep strategy:

Longer form articles rich with insights:

• Storytelling to Strategize — Strategic Thinking Institute — The power of storytelling in leadership and innovation, emphasising visualisation, planning, and a supportive environment for radical thinking. Strategic relationships drive growth.
• Speed up your strategic planning — part one: market segments — Center for Simplified Strategic Planning — Efficient strategic planning through targeted market segmentation leads to cost savings, clearer strategy development, and enhanced customer value differentiation.
• Healthcare’s digital future — Mckinsey on Marketing, Tech and Sales — Healthcare IT integration has evolved through waves, now emphasising full digitisation. Patients of all ages are open to digital services if quality meets expectations. Key insights reveal patient demand, age inclusivity, and limitations of mobile health.
• A New Approach to Knowledge-Sharing Within Organisations — Harvard Business Review — “Revolutionise knowledge-sharing in organisations with evolvable scripts, enabling adaptable and efficient operations in the face of challenges and turnover.”
• The gen AI skills revolution: Rethinking your talent strategy — McKinsey — To help successfully plot the road ahead, this article identifies the new skills software teams will require, examines how their evolution will alter roles and risks, and reveals how companies can orient their talent management practices toward developing skills for greater flexibility and responsiveness.

Business at the point of impact:

Emerging issues and technology trends can change the way we work and do business.

• How to Regulate Generative AI in Health Care — Harvard Business Review — The rise of generative AI in healthcare requires a new regulatory approach to maximise benefits and manage risks effectively.
• The Future Of Multimodal AI In Healthcare — Forbes — Innovation — Leveraging multimodal AI in healthcare drives enhanced diagnostic accuracy, personalised treatment plans, drug discovery, patient monitoring, and advanced surgical assistance.
• How Early Movers Are Realising AI’s Promise — Forbes — Innovation — AI presents significant potential for business growth and operational efficiency, but challenges remain in deployment and workforce adaptation. Industries like manufacturing, healthcare, and retail can benefit from AI in quality control, patient care, and customer experience.
• Time Well Spent With GenAI — Forbes — Unlock new levels of productivity and innovation by integrating Generative AI in the workplace, saving time, enhancing efficiency, and reshaping job roles for the future.
• Are Organisations Ready For The Full Integration Of AI? — Forbes — Innovation — Key Insight: Organisations recognise the critical role of AI in enhancing productivity and customer experiences, but face challenges like data privacy concerns and the need for human oversight.
• Opportunities, Challenges, And The Future Of AI In The Creator Economy — Forbes — Innovation — AI is revolutionising the creator economy by enabling virtual influencers, enhancing content production efficiency, and providing valuable audience insights for brands.
• AI may change your job but it won’t eliminate many, labour experts say — Fortune | FORTUNE — AI is transforming job functions, enhancing productivity, and creating new opportunities without leading to mass unemployment.

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