"Business" vs "AI" or "ML"

"Business" vs "AI" or "ML" is always a better option until, used for right path or vision or with trustful leadership group. Opposite to this, if we will not do, it might be the turning point of our Retrenchment & competitor's escalation at same time.        

I am greatfull like someone in my webinar asked a query of everyone's intrest now a days. I would like to share with you all for better understanding & knowledgeable in front of such techees.

Question from XYZ Company owner: "AI" can faster in technology implementation but not the business environment if use accordingly obviously. How non-technical business persons or management should be aware to avoid any influence be other technology leaders, just to put thier short term values & fetch the earning from companies bucket now a days it's a income & secure their position only moreover than vision to company’s growth where they appointed.

My Reply & Recommendations : What a thought-provoking question!

You're absolutely right. AI and automation have significantly accelerated the pace of technological advancements, but the pace of change in the business environment has not kept up with the same speed. This creates a chasm between the technical capabilities and the business's ability to adapt.

Non-technical business leadership or management need to be aware of this disparity to ensure they stay relevant and secure their position in the industry. Here are some key takeaways for non-technical visionary:

1. Embrace digital literacy: Develop a basic understanding of technology and its impact on your industry. This will help you make informed decisions and communicate effectively with your technical teams.

2. Stay informed about AI trends: Follow industry leaders, attend conferences, and participate in online forums to stay updated on AI developments and their potential applications in your field.

3. Focus on strategic alignment: Understand how AI can enhance your business strategy, rather than just focusing on technical implementation. Identify areas where AI can drive value and prioritize accordingly.

4. Develop a culture of innovation: Encourage experimentation, iteration, and learning from failures within your organization. This will help your team stay agile and adapt to changing market conditions.

5. Foster collaboration: Build strong relationships with your technical teams, data scientists, and other stakeholders to ensure that you're aware of their capabilities and limitations.

6. Prioritize data-driven decision-making: Emphasize the importance of data analysis and visualization to inform business decisions, rather than relying solely on intuition or anecdotal evidence.

7. Develop soft skills: Focus on developing skills like communication, problem-solving, and critical thinking, which will become increasingly valuable in an AI-driven business environment.

8. Stay adaptable: Be prepared to pivot your strategy if AI adoption doesn't yield the expected results or if new technologies emerge that disrupt your market.

9. Lead by example: Demonstrate your commitment to digital transformation by embracing new technologies yourself and encouraging others to do the same.

10. Upskill and reskill: Invest in training programs or mentorship opportunities that help your team develop the skills needed to work effectively with AI technologies.

By following these guidelines, non-technical business managers can position themselves for success in an era where AI is increasingly transforming the business landscape.

Remember, while AI may accelerate technological progress, it's ultimately up to humans to harness its potential and create a sustainable competitive advantage.