AI is revolutionizing the business world, but it's a bit like riding a unicycle on a tightrope stretched over a chasm filled with hidden pitfalls. Not for the faint-hearted, surely. It's not just about the glitz and glamour of tech advancements; it's about predicting and managing the risks involved.

In May 2023, AI and robotics trimmed a staggering 4000 jobs. No, this is not a dystopian sci-fi plot, but the harsh reality. While AI automates tasks, accelerates efficiency, and cuts operational costs, it can also lead to unemployment and inequality. It's crucial to understand this double-edged sword phenomenon to tackle the emerging challenges.

AI doesn't just stay in the confines of its coded world; it ripples through societies, affecting various aspects from racial and gender equality to loan approvals. Remember the Lemonade fiasco? Their AI system faced backlash for automatic claim denials based on user videos. A classic case of AI stumbling in the societal labyrinth.

Ethics isn't just about philosophy and moral science textbooks. It's a crucial aspect of AI too. AI must be navigated ethically to ensure a sustainable, equitable, and diverse society. Organizations like Microsoft have laid out a journey towards AI ethics, and documents like the 'Blueprint for AI' or the AI Risk Management Framework by NIST are guiding stars in this expedition.

Too much, too soon? That's precisely what some advocates are stating, propounding a six-month respite from AI development. Renowned figure Geoffrey Hinton's exit from Google underscores these concerns, calling for a breather in the relentless march of AI. If AI were a Hollywood movie, this would be the dramatic plot twist.

The wild west days of AI are over. Today, robust governance is crucial. Organizations must develop and implement their own governance systems to ensure safe, non-discriminatory, and ethical AI systems. Organizations like NTT DATA have even launched AI governance services. This is how serious we are about keeping AI in line.

With the Covid-19 pandemic acting as a catalyst, digitization and automation have been on a rollercoaster ride. While efficient and cost-effective, intelligent automation amplifies risks and regulatory scrutiny. The need of the hour is a holistic view of automation risks and benefits.

To handle the Jekyll and Hyde nature of intelligent automation, organizations need a dedicated center of excellence for risk-return management. This central function marries the performance and value of automation with risk management, ensuring a balanced approach.

A detailed inventory of AI and automation applications is crucial. Prioritizing processes based on organizational value and business criticality can highlight optimization opportunities. So, put on your Indiana Jones hat and get ready to identify these goldmines.

Integration isn't just about the nitty-gritty of software; it's about establishing a standardized procedure and principles for AI development and application. This ensures consistency across platforms and aids in early risk identification.

Every AI system is a potential risk terrain. A thorough and rigorous testing regime is vital to identify inaccuracies or biases. Data quality, correctness of implementation, system performance, explainability, and bias are critical assessment areas.

You've built it, but your work is far from over. Consistent monitoring of the benefits and risks of AI and automation is crucial. A well-defined performance and risk indicator system along with an issue-management procedure will help in effective remediation.

In conclusion, AI is a mixed bag of enormous possibilities and equally gigantic risks. Businesses need to walk this tightrope with a clear understanding of the risks involved and a robust mechanism to manage them. It's a thrilling, transformative journey, but one that requires constant vigilance and an unwavering commitment to maintaining balance.