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AI-Driven Business Transformation: first steps, ethics and Metrics for AI Implementation

Another meaningful conversation on AI & Business with Greg Verdino, President of VANNINO, Content consultancy, and Co-Host of No Brainer: An AI Podcast for Marketers. Author of NEVER NORMAL and micro marketing. Defined as “a trend-spotter with an uncanny ability to predict the future.

Even this time, this interview has involved “burning questions”, and we have asked Greg about AI-Driven Business Transformation, which needs careful consideration of the overarching aspects of AI over single applications in the business.

What are the key first steps a business should take for an AI transformation?

Organisational Readiness and Approach

Exploration Stage: Many companies are currently in the early stages of exploring AI technologies. Senior employees actively learn and gather information, while junior employees may independently experiment with AI tools without proper oversight. This shows that organisations are still in the process of getting familiar with AI and figuring out how it can be useful to them.

Use Case Definition: Before diving into AI implementation, it's important for organisations to define practical uses for AI clearly. This means identifying specific areas where AI can automate or improve tasks to make them more efficient and effective. It also involves using AI for innovative purposes, like gaining better insights into customers or creating personalised content on a larger scale. Defining use cases helps establish a solid starting point for using AI.

Data Preparation: One key consideration is ensuring organisations have the necessary data for their AI use cases. However, data is often stored in different departments and may have ownership and accessibility challenges. This means that collaboration and coordination are crucial to overcome these obstacles and make data available for AI projects.

Collaboration and Alignment: Successful AI implementation requires collaboration and alignment among different people involved in an organisation. Business owners must clearly communicate their goals, while technical experts contribute their knowledge and skills to bring them to life. Effective communication and collaboration between these groups ensure that AI projects align with the organisation’s overall objectives.

What are the elements businesses should manage when implementing AI.?

Responsible Use Policy: To address the risks associated with AI, organisations should establish a policy that guides its responsible use. This policy sets clear boundaries and guidelines for how AI should be used, protecting the organisation and its employees. It aims to strike a balance between controlling potential risks while allowing individuals to explore and innovate with AI within defined limits.

AI Ethics Board: Considering the formation of an AI ethics board is crucial. This board can be made up of internal members or external experts who provide impartial guidance and support. Its role is to help the organisation navigate ethical challenges, assess potential risks, and make informed decisions about how to use AI responsibly.

Bias and Fairness: Organizations must be mindful of biases that may exist in AI systems. AI algorithms can unintentionally perpetuate biases based on race, ethnicity, or gender, leading to negative outcomes. It's important to address these biases and ensure fairness in AI-driven decision-making. Organisations should also be cautious about potential intellectual property issues related to AI-generated content.

What are the metrics for evaluating the impact of AI on business?

Business Metrics: Evaluating the success of AI implementation involves measuring key business metrics. These metrics can include improvements in efficiency, financial impacts like increased profits, speed of innovation, and enhanced productivity. By tracking these metrics, organisations can assess AI’s tangible benefits to their overall performance and profitability.

Employee Engagement and Satisfaction: It's crucial to assess the impact of AI on employee productivity, engagement, and job satisfaction. Organisations should consider whether AI implementation has improved the work environment and made employee tasks more engaging. This evaluation helps ensure that AI technologies increase efficiency and positively impact employees' experience within the organisation.

Customer Satisfaction and Brand Reputation: Another important aspect is evaluating how AI has affected customer satisfaction and the organisation’s brand reputation. Organisations should examine how AI implementation has influenced customer service, marketing efforts, and overall customer perception. By considering these factors, organisations can determine if AI has successfully enhanced customer experiences and strengthened their brand reputation.

, Thank you, Greg Verdino, for your insights and time!


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