Andreas Welsch explores how companies can achieve real impact by addressing customer pain points with a gradual, agile approach to AI adoption and go-to-market strategies.
Copyright: intelligencebriefing.substack.com – “The Art Of Selling AI—Without Selling AI”
On October 17, Nicole Wieberneit (Sales & GTM Executive) joined me on “What’s the BUZZ?” and shared how you can scale go.-to-market (GTM) for enterprise Generative AI. Software companies often struggle to cut through marketing hype and focus on practical applications that truly add value. Product organizations need effective strategies that avoid pilot paralysis, adopt customer-focused go-to-market approaches, and scale AI projects effectively. But, where should you start? Here is what we’ve talked about…
Addressing Real Customer Problems
AI’s potential isn’t fully realized when the focus remains on novelty rather than on solving pressing, real-world issues. Identifying and addressing specific problems, especially those that keep business decision-makers up at night, is the most effective way to ensure AI projects don’t lose momentum.
Many companies get caught up in exploring AI’s “art of the possible,” brainstorming endless applications without enough focus. This approach often leads to analysis paralysis and delays in tangible results. By zeroing in on practical, high-value use cases, teams can ensure that AI initiatives are grounded in solving core business needs.
A more successful approach is to prioritize high-impact use cases within key verticals. For example, in the financial services industry, where compliance and data management are crucial, AI can be especially effective in automating document processing or handling regulatory workflows. These types of applications address significant operational pain points while allowing teams to start small and build momentum.
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Instead of attempting to reinvent processes across the board, organizations can concentrate on areas where AI has a clear, measurable impact. Focusing on these areas allows for early successes that can build organizational support and provide a foundation for broader AI adoption over time.[…]
Andreas Welsch explores how companies can achieve real impact by addressing customer pain points with a gradual, agile approach to AI adoption and go-to-market strategies.
Copyright: intelligencebriefing.substack.com – “The Art Of Selling AI—Without Selling AI”
On October 17, Nicole Wieberneit (Sales & GTM Executive) joined me on “What’s the BUZZ?” and shared how you can scale go.-to-market (GTM) for enterprise Generative AI. Software companies often struggle to cut through marketing hype and focus on practical applications that truly add value. Product organizations need effective strategies that avoid pilot paralysis, adopt customer-focused go-to-market approaches, and scale AI projects effectively. But, where should you start? Here is what we’ve talked about…
Addressing Real Customer Problems
AI’s potential isn’t fully realized when the focus remains on novelty rather than on solving pressing, real-world issues. Identifying and addressing specific problems, especially those that keep business decision-makers up at night, is the most effective way to ensure AI projects don’t lose momentum.
Many companies get caught up in exploring AI’s “art of the possible,” brainstorming endless applications without enough focus. This approach often leads to analysis paralysis and delays in tangible results. By zeroing in on practical, high-value use cases, teams can ensure that AI initiatives are grounded in solving core business needs.
A more successful approach is to prioritize high-impact use cases within key verticals. For example, in the financial services industry, where compliance and data management are crucial, AI can be especially effective in automating document processing or handling regulatory workflows. These types of applications address significant operational pain points while allowing teams to start small and build momentum.
Thank you for reading this post, don't forget to subscribe to our AI NAVIGATOR!
Instead of attempting to reinvent processes across the board, organizations can concentrate on areas where AI has a clear, measurable impact. Focusing on these areas allows for early successes that can build organizational support and provide a foundation for broader AI adoption over time.[…]
Read more: www.intelligencebriefing.substack.com
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