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Learn how AI can unlock productivity, according to AI founder Andrew Louder - The Intercom Blog
Summary
AI founder Andrew Louder explains that the days of AI being unattainable are over, with accessible off-the-shelf tools available. He illustrates this with a law firm client that reduced e-discovery work from nearly 1,000 hours per case to about 40-50 hours using AI. Louder advises that the build-versus-buy decision depends on awareness of existing solutions and requirements. He emphasizes that change management, including awareness, communication, and training, is crucial for successful AI adoption. According to Louder, businesses should conduct AI readiness assessments, establish data management plans, and build robust knowledge bases to ensure AI effectiveness.
Context
The Intercom Blog publishes a podcast transcript featuring Andrew Louder, founder and CEO of Louder Co., a consultancy that helps businesses develop AI strategies. Louder discusses how recent advances in generative AI have made off-the-shelf AI tools accessible and cost-effective for improving productivity. He shares a case study of a criminal defense law firm that reduced e-discovery work from nearly 1,000 hours per case to about 40-50 hours using an AI tool. The conversation covers build-versus-buy decisions, change management, AI readiness assessments, and data governance as critical factors for successful AI adoption.
Approach / What changed
Louder recommends conducting an AI readiness assessment to identify pain points and quick wins, then deciding between building custom AI or buying off-the-shelf tools based on specific needs and available solutions. Key steps include investing in change management (awareness, communication, training), implementing a data management plan, and building a robust knowledge base with accurate data and policies. Minimizing risks involves assessing requirements, comparing systems, prioritizing configurable tools, and writing an AI policy.
Takeaways
A law firm reduced e-discovery work from nearly 1,000 hours per case to about 40-50 hours by implementing an AI tool called Nextpoint, demonstrating massive productivity gains with AI-plus-human validation.
The decision to build or buy AI solutions depends on awareness of existing tools and specific requirements; off-the-shelf solutions are now more accessible and often preferable to costly custom builds.
Successful AI adoption requires more than tool selection—it demands change management across the organization, including awareness campaigns, communication, and training, as well as a solid data management plan and knowledge base.
FAQ
How can I decide between building or buying AI solutions?
Louder explains that awareness of existing tools is key. If you don't know what's available, you may gravitate toward building, but off-the-shelf tools are now more accessible and often more cost-effective. The decision hinges on requirements, processes, and whether a suitable tool exists.
What are the biggest risks when adopting off-the-shelf AI tools?
The post lists risks such as choosing a tool that doesn't fit, poor change management, and lack of data governance. To minimize risks, Louder advises assessing requirements, comparing systems, prioritizing configurable tools, investing in change management, and writing an AI policy.
What steps should I take to prepare my business for AI?
Louder recommends starting with an AI readiness assessment to identify pain points and quick wins. Then, implement a data management plan and build a robust knowledge base with accurate data, policies, and documentation. Change management across the company is also critical for adoption.
Source and freshness
- Source
- intercom.com
- Published
- Added to Yomu
Summaries are generated from the original by a language model. Check the original before relying on it.
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