If AI is to matter in the economy, it must first matter to small businesses. Firms employ over 61 million people, nearly half the private workforce, yet most run on outdated technology. While smartphones update monthly, many small businesses still use systems built a decade ago.

Search fund entrepreneurs bridge this gap by upgrading established firms with modern tech. One deal turned a 50-person roadside assistance firm into Asurion, now a global tech-care provider. Others have scaled compliance firms into nationwide SaaS platforms.

Generative AI now accelerates these transformations, cutting work times by over 60% across supply chains, compliance, and document processing functions. Complex tasks can now be completed in hours, unlocking double-digit productivity gains and allowing small businesses to focus on growth.

Search funds are not the only path forward. AI consulting firms, tech studios, and AI-powered roll-up strategies bring enterprise-grade tools to family-run firms. For communities that have relied on traditional playbooks, decades of growth can be compressed into months.

The cost of AI has never been lower, and the opportunity is wide open. Once deployed at scale, AI could power a wave of productivity on Main Street, helping small businesses compete and strengthening the economy for half of their workforce.

Would you like to learn more about AI, tech, and digital diplomacy? If so, ask our Diplo chatbot!

Artificial intelligence (AI) is an important subject to Nick Soggu, CEO of SilverTech, a Bedford-based digital experience agency.

AI is near and dear to Soggu not only as SilverTech expands its business pursuits with the recent purchase of another tech company, Paragon, but also personally to Soggu as he works toward a doctorate degree in AI and machine learning.

AI has far-reaching consequences for business and for society as a whole, according to Soggu.

“The ethics and the threat side of things is very real. I think as these reasoning models are being created and now start to get more advanced, they do take on interesting types of personalities,” Soggu said.

“These models are getting to that level of thinking and cognizant behavior capabilities, where they’re starting to do more than regurgitate facts and provide the next best word fit,” he added.

Enhancing the use of AI was cited as one of the benefits cited in SilverTech’s recent purchase of Paragon, which is based in Ohio and brings to the table a broad client list that deepens SilverTech’s portfolio.

SilverTech’s headcount, as a result of the purchase, grew from around 85 to about 150, making it “uniquely positioned to lead innovation and drive transformative growth in the tech sector,” according to the statement that announced the purchase July 24.

Soggu said there were two primary reasons for the Paragon purchase: one technical, one strategic.

The technical part has to do with what Soggu called “digital experience products,” otherwise known as content management systems (CMS products such as WordPress) or digital experience platforms (DXPs).

“Paragon happens to be in a market providing the same types of services we do, but they’re working with a whole different set of these digital experience solutions. And so what you have is the best of both worlds when you combine the two firms,” said Soggu.

Strategically, said Soggu, Paragon had clients in certain areas that SilverTech did not.

“They work with just like we do with a variety of brands that are different than we are, in verticals that are different than we are. And at the end of the day, it’s a diversification strategy in the client concentration,” said Soggu. “They don’t work with a lot of banks and credit unions that we do, as an example, but they have a lot of direct-to-consumer type brands like Ugg and brands of that nature that they’re providing services for. And so it expands our customer hopeful portfolio as well.”

The AI component adds some horsepower to the organization, according to Soggu.

“The future is really about what we’re going to be doing together using artificial intelligence and machine learning technologies for our client base, and the combined horsepower, from an engineering perspective, that we’re able to bring to the table,” said Soggu.

According to the company, the combined strength of the companies offers the following benefits:

Scale the delivery of AI-powered personalization, predictive analytics and intelligent search.

Accelerate innovation in machine learning, conversational interfaces and process automation.

Deepen customer research and deliver digital strategy that is aligned with business strategy.

Expand CMS and DXP platform expertise with top-tier technology partnerships and solutions, and is certified and well credentialed in Sitecore, Progress Sitefinity, Kentico, Hubspot, Contentstack, Contentful, Salesforce, Sanity and Big Commerce.

“This acquisition brings together Paragon’s deep enterprise experience and consulting expertise with SilverTech’s strengths in digital marketing, media and managed services,” said Jeff McPherson, chief growth officer at SilverTech. “Together, we are expanding our ability to serve a broader range of markets with a powerful mix of strategic insight and technical innovation — helping clients harness data, personalize experiences, improve decision-making and drive automation.”

In that growing use of AI, there are threats and opportunities, as Soggu has studied both as a tech executive and PhD student.

“The world of deep fakes and the world of creating content that looks and feels like human created content — and it’s very compelling content — that’s a dangerous and slippery slope,” said Soggu. “I think there’s a lot, from an ethics perspective, that’s yet to be determined, things that we should be certainly concerned about.”

At the same time, according to Soggu, AI can produce efficiencies that ultimately benefit a business.

“The opportunities are very compelling in terms of efficiency gains, in terms of work output gains,” he said. “Large corporations are seeing upwards of 30% to 50% gains in efficiency and work output.”

In his work, Soggu said AI can be applied to some quality assurance tasks.

“We can put a website through its paces using AI tools and technologies to do user testing much more efficiently and effectively than we can with five or six humans involved in that process,” Soggu said.

From boardrooms to shop floors, companies are moving quickly to embed AI into their operations. The goals are clear: drive efficiencies, reduce costs, and deliver smarter, faster, more personal customer experiences.

This makes a lot of sense given that today 89% of businesses are expected to compete primarily on CX. However, the results aren’t always matching the hype.

A recent Gartner study found that while enterprise AI adoption is rising, real impact is often elusive. The reason? Many businesses are still operating with disconnected systems and disjointed data. Without a strong foundation, AI can’t deliver what it promises.

Siloed systems aren’t just a technology problem—they’re a business barrier.

The CX Disconnect: When Fragmentation Undermines Intelligence

Too many organizations still rely on a patchwork of tools for customer experience, supply chain, finance, and HR. While these point solutions solve individual challenges, they create friction and disconnect across the business. In an AI-powered world, friction is the enemy.

AI thrives on complete, clean, and contextualized data to function effectively. If your marketing, sales, service, and fulfillment teams cannot see the same data in real time, or trust that it’s accurate, your AI strategy will not be set up to succeed.

With the best intentions to embrace AI in an effort to achieve incredible efficiency, instead, customers will still lose valuable time on manual integration, inconsistent customer experiences, and AI outputs that are only as good as the (fragmented) data feeding them. The delightful experience aspirations turn into trust lost and frustration all around.

Modular Innovation, Meet Enterprise Intelligence 

SAP has reimagined enterprise management with SAP Business Suite, representing a fundamental shift from traditional ERP systems to a modular, composable architecture that integrates AI, data, and applications into a unified platform.  

Grounded in harmonized, semantically rich data, this architecture allows businesses to make sense of data that has traditionally been scattered across systems and trapped in silos, so AI has the comprehensive data it needs to quickly generate meaningful insights.

SAP Business Data Cloud (SAP BDC) with native integration of SAP Databricks, serves as a data backbone for business AI. It seamlessly connects all SAP data and third-party data and provides integrated governance to enable real-time AI-driven decision making.  

Companies do not lose precious time locating and preparing data for AI. AI systems work on trusted, contextualized data, not just generic data. This produces accurate, reliable, and actionable AI recommendations that enable organizations to scale AI innovation rapidly across business domains. 

SAP BDC is the foundation for Joule, SAP’s AI copilot that acts as an intelligent orchestrator across the entire business suite. SAP BDC ensures that Joule has structured business context for natural language processing and that its outputs are accurate so that Joule can provide always-on assistance to break down silos between business operations. 

For example, when a customer service or sales representative handles a complex order issue, Joule can: 

• Check real-time supply chain constraints

• Respond to RFPs faster
• Personalize the response by pulling in relevant customer history from CRM systems
• Speed response with automated case routing and research

The results are faster resolutions, happier customers, empowered employees, and incredible business outcomes with less effort and overhead.

CX + AI + ERP = Real Results

Integrating CX AI with core ERP systems enables end-to-end process optimization that was previously impossible with fragmented systems. When CX systems connect natively to back-office systems, organizations gain: 

• Real-time personalization powered by operational data
• Intelligent workflows that prioritize high-value customers
• Predictive insights that help teams act before issues arise

The numbers speak for themselves. According to an Enterprise Strategy Group report, customers using this approach reported these benefits:

• Up to 60% reduction in the number of issues service and support teams deal with due to fewer manual errors, automated self-service support functions, automated self-service, and AI chatbots
• 25% to 50% improvement in time to resolution for issues that did require service or support resources
• 25% to 70% improvement in productivity of digital marketing and customer operations teams
• 50% to 90% improvements in sales team productivity by offloading smaller transactional sales, faster quote generation, and streamlined order management
• 20% to 40% increase in productivity of business operations due to less time spent on invoices, payments, shipments, and returns and more informed decision-making

This is not just incremental change; it’s enterprise transformation, driven by customer needs and powered by AI.

The Future of Intelligent Enterprise Operations 

Embedded CX AI within a composable business suite represents a bright future that takes the possibility of AI and makes it a reality. 

• Businesses can seamlessly orchestrate intelligence across all functions, delivering experiences that feel effortless to customers while optimizing operations behind the scenes. 
• Artificial intelligence won’t just automate individual tasks, but also orchestrate entire business ecosystems to deliver superior outcomes.  
• Maintaining enterprise-grade reliability and enabling modular innovation will allow organizations to adapt to changing market conditions while creating competitive advantages. 

With the rise of AI, businesses face a pivotal moment in time. Taking advantage of all that technology has to offer demands more than point solutions and departmental optimizations; it requires unified platforms, complete clean underlying data, and a clear unified strategy.

Jessica Keehn is chief marketing officer of SAP Customer Experience.