We will successfully embrace human-AI co-evolution once we draw the line between differences in human and artificial intelligence and delegate decisions to AI accordingly.

As both humans and AI evolve, so do all the processes, institutions, rules, standards, and regulations related to their interaction.

AI product is a companion to a customer, interacting at their edges of intellectual capabilities where a customer seeks their own advantages to AI leading to realizing true, unique human potential - the ultimate measure of an AI product’s success.

As AI learns from customer interactions, customers evolve into co-developers of the product, inherently becoming co-decision-makers. An essential progression is to educate customers on how they can contribute to product improvement and actively engage them in organizational decision-making processes.

Every human’s responsibility is to develop and empower themselves further, but it is in the best interest of the organization to provide a supportive environment for its team members. Each empowered individual empowers the team, organization, and customers in turn.

Every individual possesses a moral compass and can make ethical judgments, but ethicists undergo specialized training to make those judgments systematically, making them particularly effective in high-risk AI products and complex or hazardous situations.

Asking good questions is halfway through better decisions in each product development stage: Proof of Concept, development, deployment, and scaling. It is a skill that can be learned. Good questions help reevaluate AI products for alignment in each development stage.

Time and space dedicated to deep thinking and focused work can produce breakthrough ideas and solutions. It is the most valuable practice of human endeavor. It is in organizations’ best interest to encourage it and provide a supportive environment for this.

Decision-making is a skill that can be learned and improved. Organizations and individuals can enhance their decision-making capabilities through various methods, including collective intelligence, decision-making theories, data and AI itself.

A multidisciplinary team is a step forward but when each individual has basic interdisciplinary education they better communicate with other team members and are able to participate in deep-dive team discussions around the specific contexts of AI products, their impact, benefits, and risks.

Accelerating AI’s progress depends on accelerating human intellectual progress, essential for accommodating swiping technological change. Smarter customers make AI smarter, improve their interactions with AI, and reduce their own vulnerability to hazardous situations leading to higher social acceptance of AI technologies.    

The more responsibility and care organizations take for building AI products, the less governments will have to regulate. Proactive engagement with the AI governance field to exchange knowledge and collaboration with other organizations is essential for building beneficial AI products as well as for a healthy AI ecosystem.

A genuine AI companion guides the customer toward answers rather than imposing them; provides accurate information for factual queries; supports better life decisions without making those decisions on behalf of the customer; handles mundane tasks to free up space for the customer to focus on more meaningful, exploratory questions.

Trust operates in 3 dimensions: the more agency and decision-making power customers have, and the safer AI products are the higher customer trust; managers trust employees the more effort, accountability and accomplishments they demonstrate; customers, employees, and managers individually trust their own decisions by accessing relevant knowledge and continuous practice of decision-making.

As AI in the digital space blurs physical borders, it becomes essential for governments to seek common ground on regulations and standards. In contrast, companies tend to adopt this collaborative approach more organically; frequently, the most popular features in one AI product are adopted by others, driven by customer demand.