Making AI Practical and Profitable for Real Businesses With Ken McLoud
カートのアイテムが多すぎます
カートに追加できませんでした。
ウィッシュリストに追加できませんでした。
ほしい物リストの削除に失敗しました。
ポッドキャストのフォローに失敗しました
ポッドキャストのフォロー解除に失敗しました
-
ナレーター:
-
著者:
概要
Ken McLoud is the Founder of Laconic Technology, a technology company focused on helping businesses harness the power of artificial intelligence and custom software to streamline operations, boost efficiency, and unlock growth. Drawing on his experience in AI engineering and strategic consulting, he partners with clients to design solutions that integrate smoothly with existing systems and deliver measurable business results. Prior to founding Laconic Technology, Ken worked as a Design Engineer at Ruger Firearms, where he leveraged his technical expertise to develop innovative products.
In this episode…Artificial intelligence is everywhere right now, but most conversations still revolve around tools, prompts, and hype. So what actually happens when a company stops chasing AI trends and starts using the technology to solve real business problems?
According to Ken McLoud, a seasoned engineer who has spent years building complex systems, the first step is shifting the question entirely. Instead of asking where they can deploy AI, businesses should start by identifying the real constraint in the system and attacking that problem directly. In practice, that often means automating repetitive tasks, improving lead generation, or building systems that analyze opportunities and make smarter decisions at scale. When companies focus on the right problem first, AI becomes a practical tool for measurable impact rather than a shiny experiment.
In this episode of In Good Company: Where Relationships Drive Results, Lisa Kilrea is joined by Ken McLoud, Founder of Laconic Technology, to discuss how businesses can implement AI in ways that actually drive revenue and efficiency. Ken explains why "we need AI" is often a red flag, how custom systems differ from simple AI integrations, and where B2B companies are missing the biggest opportunities. Ken also shares advice on identifying the real business constraints AI should solve.