Artificial Intelligence (AI) has transformed the business landscape, from automating mundane tasks to making critical decisions. Yet, this powerful tool comes with its own Pandora's box of ethical dilemmas, such as biased algorithms and invasion of privacy. In this whirlwind of advancement, where do we draw the line?

AI isn't inherently evil, but its misuse or mishandling can lead to disastrous consequences. Instances of racial bias in digital ads, biased credit limit decisions, and inaccurate medical diagnoses are testament to how AI can go awry. Hence, the urgent call for Responsible AI: a principle-driven, holistic approach to uphold ethical standards in AI development and application.

Many companies grapple with a yawning chasm between the principles of Responsible AI and their actions—the so-called "Responsible AI Gap." Yet, when the gap is bridged, the rewards can be manifold: improved market share, boosted profitability, and enhanced trust among stakeholders. Major tech players like Google, Microsoft, and Salesforce are already reaping these benefits by demonstrating their commitment to Responsible AI.

An ethical work environment nurtured by Responsible AI can also be a magnet for top digital talent, reducing employee turnover. After all, who wouldn't prefer to work in an organization that respects their values and upholds ethical behavior? The drive towards Responsible AI isn't just about risk mitigation—it's also about fostering a culture where ethics matter.

So how can companies ensure a seamless transition to Responsible AI? It starts with appointing a chief AI ethics officer and instituting a diverse Responsible AI committee. This leadership should drive the development of clear AI principles, policies, and training programs that resonate with company values. Further, they should integrate human + AI governance in their products and services, conduct regular Responsible AI reviews, and implement tools and methods to help AI developers handle ethical issues effectively. Finally, they should create and test response plans to mitigate adverse impacts from AI-related issues.

Implementing Responsible AI isn't an overnight process—it's a gradual commitment that ensures ethical use of AI while meeting business objectives. However, this commitment can pave the way to improved trust, financial performance, and talent attraction, thus fostering an environment conducive to sustainable growth.

Given the complexity and multidimensional nature of ethical issues in AI, the role of an AI Ethicist is critical. However, a team-based approach, where insights from experts across different disciplines are integrated, can offer a more comprehensive solution. This approach mirrors the evolution of data science roles into specialized teams and underscores the need to manage ethical risks as a top priority.

Organizations need a pioneer at the helm, like a Chief Trust Officer, to champion AI ethics across the business. Their key responsibilities should include improving AI engineering with ethical perspectives, advising on ethical practices, and ensuring accountability. With unethical AI behavior potentially leading to lawsuits, fines, and reputation damage, it's crucial for companies to address AI ethics proactively, whether through an individual or a team-based approach.

In conclusion, as businesses increasingly depend on AI systems, it's imperative to prioritize AI ethics to mitigate risks and ensure ethical AI behavior. Navigating the intricacies of AI ethics effectively, either through an individual or a team-based approach, will not only serve as an ethical compass but also ensure long-term business success.