Mid-Market Executives Must Prioritize Process Over People and Technology in AI-Driven Operations – Alex Castro, 11:59
By Lane F. Cooper, Editorial Director, BizTechReports
Mid-market executives must shift their focus from technology adoption and workforce changes to reengineering core business processes as artificial intelligence (AI) reshapes industries at an unprecedented pace, according to Alex Castro, CEO of 11:59 (https://www.1159.ai/).
Speaking in a recent BizTechReports vidcast, Castro emphasized that while AI tools and talent are essential, they are secondary to the fundamental restructuring of operational workflows.
“While employees come and go, and AI technology evolves every few months, a company’s unique processes remain its most valuable asset. AI’s true power lies in optimizing and automating these workflows, allowing businesses to enhance efficiency, reduce costs, and deliver faster, more responsive services,” he said.
Companies that embed AI into their operations today will continuously refine their models, making it increasingly difficult for late adopters to catch up without significant investment.
“That is why, in today’s rapidly evolving AI landscape, the value of mid-market businesses is no longer in their technology or even their people—it’s in their processes,” Castro stated. “Companies that understand how to refine and automate their unique operational workflows will have a sustainable competitive edge, while those that focus solely on AI tools will struggle to keep up.”
AI’s Growing Impact on Mid-Market Business Models
Unlike large enterprises with dedicated AI strategy teams and deep pockets, mid-market firms often lack the resources to experiment with unproven AI investments. This puts them at risk of falling behind as AI-driven competitors redefine customer expectations.
Castro cited a striking example in the legal industry: law firms that integrate AI-driven document automation will soon generate complex legal documents, such as trusts, within 48 hours instead of six to eight weeks—at a fraction of the cost.
In the construction industry, AI-driven predictive analytics transform project estimation and logistics management. Leading firms can now generate highly accurate cost and timeline estimates within 24 to 48 hours, compared to the traditional two- to three-week process. AI also enhances logistics planning, ensuring materials, equipment, and labor are coordinated with greater precision.
“If your competitor can deliver an accurate bid in days while you still take weeks—with fewer cost overruns and change orders—your ability to compete will erode quickly. This is not because of AI itself, but because your processes remain outdated,” he stated.
A New Approach: Process-Led AI Integration
To stay ahead, Castro outlined a three-phase approach that mid-market companies should follow when implementing AI:
Operational Efficiency First – To reduce inefficiencies, leaders should automate backend workflows, such as invoice processing, data entry, and internal approvals. Companies can achieve ROI within 60 days by identifying bottlenecks and streamlining core workflows.
Customer Experience Optimization – Implement AI to enhance how customers interact with the business, including automated responses, predictive engagement, and streamlined order management.
Sales and Marketing Enhancements – Only after optimizing operations and customer experience should firms explore AI-driven lead generation, customer insights, and predictive sales strategies.
“Many mid-market firms are being pitched AI solutions that focus on sales and marketing automation first,” Castro noted. “That’s the wrong starting point. If your internal processes are inefficient, AI won’t fix that—it will just amplify inefficiencies.”
The Risk of Delayed AI Adoption and the Rising Cost of Inaction
A key challenge for mid-market companies is the slower AI adoption cycle compared to large enterprises. While Fortune 500 firms deploy AI solutions within 90 days, mid-market firms take an average of 270 days to make similar investments. This gap, according to Castro, could prove fatal.
“If you wait another 30 months to implement AI, your ability to catch up will become exponentially more difficult,” he cautioned. “AI is a learning system—those who start early will have a significant advantage in refining their models, optimizing workflows, and responding to market changes.”
The consequences of slow AI adoption are already rippling through the economy, particularly in the labor market. Tech industry unemployment has surged from 3.4% in December to 5.9% by the end of January 2025, an increase that many analysts attribute to the rise of AI automation.
“The rapid displacement of traditional IT roles is a clear signal that AI isn’t just enhancing productivity—it’s eliminating jobs,” Castro explained. Many enterprises are automating technical roles, reducing reliance on human-led data entry, IT support, and even software development.
Mid-market firms that delay AI adoption will not only face competition from AI-optimized rivals, but they will also struggle to attract top talent as traditional IT job functions continue to shrink.
The Focus Imperative: Measure Twice Cut Once with AI Projects
Castro urged mid-market executives to identify their top three pain points, invest in AI-driven workflow automation, and focus on quick wins that generate measurable ROI within 6-12 weeks. He also warns against relying on traditional AI adoption strategies used by large enterprises.
“The top quartile of the S&P 500 is spending $500 million per year on AI, generating three major innovations annually,” he said. “Mid-market firms don’t have the luxury of trial and error. They must make targeted, high-impact investments that transform their business processes—or risk irrelevance.”
As AI continues to reshape the business landscape, one thing is clear: the mid-market’s survival depends not on AI itself but on its ability to reimagine and optimize its processes for an AI-driven world.
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