Switchboard Connect

Every other week, I curate a few relevant pieces of AI & Automation news and insights for SMB operators & execs.

Sharing just 3 items today as I think #1 is so important that I wanna keep the focus on that.

Let’s dive in.

Sometimes the words are taken right out of your mouth.

I’ve always believed Robotic Process Automation (from name brand companies like UiPath or Blue Prism) is a clunky, unreliable, expensive way to do automation. The tools & approaches you’ve heard me talking about have quickly leapfrogged this antiquated way of doing things and have paved a way for AI agents to do what RPA never could.

That’s probably why UiPath’s stock looks like this the past year:

💡 What to Know: a16z predicts that generative AI will replace outdated RPA tools, making ops automation smarter, more flexible, and easier to maintain. This shift enables businesses to automate complex workflows, reduce manual workloads, and boost ROI on operational processes.

Why it matters:

Your business likely spends significant time on ops work—tasks like data entry, document processing, or moving information between systems. These processes are essential for driving revenue and keeping the lights on, but they tie up your team in low-value, repetitive work.

The problem:

Traditional RPA tools promised automation but rarely delivered long-term value:

• High setup and maintenance costs

• Inflexibility when workflows change

• Limited ROI outside narrow use cases

The shift:

With generative AI, you can now deploy AI agents that:

• Understand your goals (e.g., “process a loan application” or “onboard a new client”)

• Adapt to unstructured data and workflow changes on the fly

• Deliver results without the complexity of RPA

The opportunity:

AI-driven ops automation is a greenfield market. There’s no dominant “ops software” player, which means a chance for businesses like yours to gain early advantages by integrating vertical or horizontal AI solutions now. This is where things are going both with the services we provide and how businesses as a whole will operate.

🔗 Read a16z’s full thesis →

💡 What to Know:

Most AI initiatives fall into a common trap—chasing vague benefits like “innovation” without a clear profit strategy. Tobias outlines a great, profit-first framework to ensure your AI projects deliver real value.

Why it matters:

AI projects often promise a mix of benefits: cost savings, better customer satisfaction, and innovation. But when soft benefits aren’t backed by clear profitability, projects can fail to meet ROI thresholds, leading to stalled initiatives.

The common mistake:

Many businesses bundle potential gains to justify AI investments, hoping they’ll add up to a viable business case. However, if the foundational profit isn’t strong enough, no amount of multipliers will save the project.

The AI Profit Stack framework:

1. Financial Impact (Foundation): Start with tangible cost savings or revenue gains.

2. Customer Experience (Multiplier): Enhance service quality, response times, and availability.

3. Process Excellence (Multiplier): Increase efficiency and reduce errors.

4. Growth Potential (Multiplier): Unlock scalability and innovation.

5. Risk Factor (Reality Check): Adjust for implementation challenges and time-to-value.

The formula:

🧾 Total Value = Profit × Multipliers × Risk Factor

Why this works:

By grounding AI projects in profit and layering benefits only when justified, leaders can confidently greenlight initiatives that drive measurable value.

🔗 Read Tobias’ full breakdown →

I’ve been playing around with Otto and it’s got a lot of potential for individuals who spend a lot of time researching, data gathering, and summarizing.

What to Know:

Otto is like having a personal data analyst on standby. It automatically pulls data from various sources, organizes it, and presents insights through customizable templates and dashboards. Whether you’re analyzing market trends, tracking KPIs, or preparing reports, Otto helps you cut through the noise and get to the insights faster.

What Otto does:

Otto provides a suite of tools for:

• Real-time data transformation: Automatically cleans and structures data from multiple sources.

• Dynamic templates: Pre-built templates like “Employment Growth Trends” help analyze hiring patterns or market movements quickly .

• Visualization and reporting: Generate dashboards that simplify tracking KPIs or trends.

Why it helps:

• Reduces human error: Automated processes mean fewer mistakes.

• Boosts productivity: Teams spend less time on repetitive tasks and more on strategic initiatives.

• Enhances decision-making: Access to clean, actionable data accelerates insights.

🔗 Check out Otto and a bunch of use cases →

That’s all for this week.

Seeing all this AI Automation news out there and not sure where to start? Feel free to reply with any questions you may have – happy to help!

Chat soon 👋