How Emerging Enterprises Can Capture Value with AI

The AI landscape has been filled with excitement and buzz, but it’s crucial to put things in perspective

The AI landscape has been filled with excitement and buzz, but it’s crucial to put things in perspective. In North America, AI adoption among businesses in the United States hovers around 50%, while Canada lags behind at less than 30%. These numbers predominantly favor larger enterprises. In this article, we’ll explore how emerging enterprises can harness Generative and Predictive AI to capture value across their value chain and gain a competitive edge against both large and small competitors.

Understanding Generative vs. Predictive AI

Generative AI: Imagine software that can create content, generate sentiment scores, assist in creative tasks like design and copywriting, or support code generation and spreadsheet analysis without explicit programming. For emerging enterprises, generative AI offers the potential to automate content creation, saving time and resources for more strategic pursuits.

Predictive AI: This branch of AI focuses on forecasting future events or outcomes through historical data analysis. Small enterprises can harness predictive AI to optimize deal conversion rates, forecast sales, and manage inventory more effectively, thereby reducing uncertainties in their operations.

AI in Action Across the Value Chain

For emerging enterprises, embracing AI might seem daunting, but starting with smaller, pragmatic use cases can reduce risk. Here are some examples:

Marketing:

  • Content Generation: Automate marketing content creation, saving time to focus on campaign effectiveness and in person audience engagement.
  • Lead Scoring: Prioritize leads based on predictive scores, driving higher conversion rates for marketing and sales teams.
  • Send Time Optimization: Use predictive AI to determine optimal communication times, enhancing open rates and engagement.

Sales:

  • Sales Forecasting: Predictive AI can augment sales teams forecast judgement by predicting close dates based on attributes on the deal and past historical deal outcomes. This can then create value in improving close rates and forecast accuracy for sales leaders & sales team members.
  • Next Best Products: With the use of predictive AI sales teams can have product recommendations prescriptively served to them, to ensure they are maximising opportunity to cross and upsell clients based on previous purchasing patterns of similar customers from the past.
  • Call Notes & Transcription: With the use of generative AI sales teams can automate the call transcription & generating meeting notes and next steps. Saving them time and allowing sales teams to focus on selling and proactively providing contextual next steps to progress active deals and identifying deal risk

Customer Success & Support:

  • Churn Prediction: Predictive AI can identify customers at risk of churning, enabling proactive retention efforts e.g (activating customer renewal marketing journey or offering promotional pricing).
  • Maximising Customer Lifetime Value: Optimise customer lifetime value by leveraging predictive AI to determine factors that can improve customer lifetime value and providing prescriptive actions to account teams. For example recommending complementary products such as an enhanced customer support package.
  • Sentiment Analysis: By leveraging Predictive and or Generative AI, teams can build out early warning signals based on signals from a variety of sources such as recent cases, customer interactions and similar customers with similar attributes, and surface recommendations to improve account health or sentiment with actions prescribed by Generative AI or predictive AI.

Finance:

  • Leveraging predictive AI finance teams can leverage predictive models to predict if a client is likely to miss a payment based on past payment patterns and similar accounts to proactively manage cash flow or engae in the dunning process earlier to improve the cash conversion times.
  • Excel Wrangling: The reality is a lot of finance teams still and will continue to leverage excel in their workflow, generative AI can be leveraged to help accelerate formula, Look Up and building out Pivot tables.

Getting Started on Your AI Journey: To embark on your AI journey successfully, consider the following steps:

  • Align with Your Organization’s Vision: Ensure AI initiatives align with strategic objectives.
  • Prioritize AI Use Cases: Focus on AI use cases that complement core goals. Weigh Business impact against level of effort to execute
  • Conduct a Maturity Assessment: Identify data and system requirements through a trusted consulting partner or in-house expertise.
  • Communicate with Relevant Stakeholders: Invest in team education and address questions or doubts around how the use of AI can augment team member roles and benefit them.
  • Invest in Technology and Services: Understand the total cost of implementation, including technology and professional services, and manage data security and regulatory risks. If you need help selecting a partner review my previous article on this topic here.

Conclusion: emerging enterprises have significant opportunities to create value for their customers and throughout their value chains by leveraging predictive and generative AI capabilities. These technologies offer a competitive edge and can significantly enhance business operations and customer experiences.

You are not alone here feel free to reach out or review more resources here:

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Written by

Ludzi Bokete

Solution Architect

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