As artificial intelligence becomes increasingly integral to business operations, companies face the challenge of implementing effective AI systems that deliver measurable value. With technology evolving at breakneck speed, designing the right architecture is crucial for long-term success. Swathi Young, a career technologist with over 20 years of experience and eight years specifically implementing AI solutions across multiple industries, offers practical insights on building AI systems that deliver both speed and business impact.
Building Practical AI Across Industries
Swathi didn’t start with AI. She’s spent over two decades as a technologist, with the last eight focused specifically on artificial intelligence. “I’ve led usage of machine learning and computer vision for lung cancer research,” she explains. Her generative AI experience includes creating a co-pilot for small business strategic planning as well as a conversational agent for a public sector website. What sets her apart is hands-on implementation experience. She doesn’t just recommend solutions – she builds them. “I lead engineering and data science teams to implement scalable, robust and secure AI solutions,” Swathi says. This practical background means she understands both the technical foundations and business realities of AI implementation.
The pace of AI development is moving at ultra speed. “Every week we hear about the advent of a new generative AI model,” Swathi points out. This rapid evolution creates both opportunities and headaches for businesses. Companies face tough questions: Which technologies will still matter in two years? How do we build systems that can adapt as technology changes? Most importantly, how do we ensure our AI investments actually pay off? Getting the architecture right helps companies navigate these challenges. “It’s very important to get return on investment of technology investments, scale as the business grows, and truly unlock business workflows and revenue streams using AI,” she says.
Three Approaches to Better AI Architecture
When designing AI systems that deliver real business impact, Swathi emphasizes practical approaches over technical wizardry.
Business First, Technology Second
Though she’s an engineer by training, Swathi doesn’t start with technology. “I start with business goals that are specific and measurable,” she insists. Examples include “increase customer retention by 50%” or “automate 40% of manual compliance workflows.” Using what she calls a “value hypothesis canvas,” teams define who will use the system, what value it creates, and how success will be measured – all before writing a single line of code.
Build Smart, Modular Systems
Effective AI consists of three layers: data, model, and serving. Each requires careful consideration. The endless build-versus-buy debate becomes particularly important with AI. “You could either leverage large language models like OpenAI’s APIs or Claude, or you can build something custom to your organization,” Swathi explains. With startups coming and going rapidly, she suggests “sticking to enterprise tools that are stable” for most implementations.
Create Feedback Loops and Build Trust
Implementation isn’t the end – it’s just the beginning. “How do you integrate feedback loops where business users are giving feedback?” Swathi asks. Equally important is transparency. She emphasizes “explainable AI where AI could be architected to be auditable and explainable to optimize trust, compliance and adoption.”
Looking ahead, Swathi sees major shifts coming. “AI might not take away your job, but those who know how to utilize AI in their industry will be the winners,” she predicts. Though millions use ChatGPT daily, she believes most organizations “have a long way to go to adopt AI.” The most profound change may be in what skills matter most. As AI makes technical implementation easier, human abilities become more valuable. “I can build an app using AI within a few minutes but human skills like networking, business development and critical thinking is what will sell the app,” she suggests.
In that world, “interpersonal skills and critical thinking come to the forefront.” For business leaders, the message is clear: don’t wait to figure out how AI fits your organization. The technology is moving fast – and the companies that adapt will have a distinct advantage.
Connect with Swathi Young on LinkedIn to explore her work in AI leadership and innovation.
