Hypothesis-driven development can mitigate the drawbacks of the rapid emergence of new ML models, as new models are being developed hourly.
New ML models emerge hourly but hypothesis-driven development can help mitigate drawbacks.
Read more about it on Towards Data Science.
The Inflation of AI: Is More Always Better?
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Practical Solutions:
- Identify Automation Opportunities: Locate key customer interaction points that can benefit from AI.
- Define KPIs: Ensure your AI endeavors have measurable impacts on business outcomes.
- Select an AI Solution: Choose tools that align with your needs and provide customization.
- Implement Gradually: Start with a pilot, gather data, and expand AI usage judiciously.
For AI KPI management advice, connect with us at hello@itinai.com. And for continuous insights into leveraging AI, stay tuned on our Telegram channel or follow us on Twitter.
Spotlight on a Practical AI Solution:
Consider the AI Sales Bot from itinai.com/aisalesbot. It is designed to automate customer engagement 24/7 and manage interactions across all customer journey stages.
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