At Built2Buy, we believe that understanding the real-world challenges manufacturers face is the first step toward solving them. Before talking about what we’re building, it’s important to talk about why we’re building it — and that begins with listening to what the data says. Over the past few years, an increasing number of respected organizations, research institutions, and technology leaders have published studies that all point to the same conclusion: manufacturers and wholesale distributors are lagging far behind other sectors when it comes to digital transformation.
We’ve gathered several of the most relevant and recent studies here, from the Auburn University ICAMS Smart Manufacturing Adoption reports to Deloitte’s 2025 Smart Manufacturing Survey, along with supporting research from SAP, Epicor, and others. Collectively, these reports show a consistent pattern — one that’s both sobering and full of opportunity. Manufacturers aren’t ignoring technology; they’re struggling with decades of entrenched systems, complex operations, and limited digital infrastructure that make modernization daunting.
The article that follows doesn’t just summarize the data. It brings these studies together to tell a shared story — a story about an industry that’s ready for transformation, but still searching for practical ways to begin. These findings form the backbone of why Built2Buy exists, and why the coming decade could be the most transformative period in manufacturing since the industrial revolution itself.
Targeted Studies / Reports (Manufacturers & Wholesalers)
- “SMART MANUFACTURING ADOPTION STUDY 2024” (Auburn / ICAMS)
- Summary: Tracks adoption levels of smart manufacturing technologies (AI, automation, IoT, predictive analytics) across U.S. manufacturers, showing SMMs lag behind larger counterparts. Auburn Engineering
- “SMART MANUFACTURING ADOPTION STUDY 2023” (Auburn / ICAMS)
- Summary: Among small- and medium-sized manufacturers, adoption of advanced tech is still nascent; many are in early awareness or evaluation stages. Auburn Engineering
- “2025 Smart Manufacturing and Operations Survey” (Deloitte)
- Summary: Survey of 600 manufacturing executives shows many manufacturers struggling with talent, legacy systems, and change management in pushing “smart operations.” Deloitte
- “Driving Growth for Midsize Wholesale Distributors” (NBS US, ~2022–23)
- Summary: 62% of midsize distributors say digital transformation must accelerate; many admit that legacy systems prevent capturing new revenue opportunities. NBS
- “Wholesalers look to analytics and AI for growth” (SAP Insights, 2024)
- Summary: In a survey of 860 wholesale/distribution firms, many cite lack of integration and weak internal systems as barriers to analytics / AI adoption. SAP
- “Practical Ways AI Is Transforming Wholesale Distribution” (Epicor, 2025)
- Summary: 83% of distribution executives say they’ve adopted AI in at least one function, but many started recently — signaling that adoption is emerging but behind; many firms still run on older systems. Epicor
Adjacent / Supporting Studies (Manufacturing or SMEs broadly)
- “Determinants of digital technology adoption in innovative firms” (Faiz et al., 2024)
- Summary: Focuses on SMEs and what holds them back in adopting digital technologies, including resource constraints and risk aversion — relevant to small manufacturers. ScienceDirect
- “Research on the impact of digital transformation in manufacturing enterprises” (Wang et al., 2024)
- Summary: Shows that digital transformation in manufacturing significantly improves production efficiency, but many firms haven’t yet made deep transformations. ScienceDirect
- “AI in Manufacturing: Market Analysis and Opportunities” (Abdelaal et al., 2024)
- Summary: Tracks AI adoption among manufacturers; in Germany, AI adoption rose from 6% in 2020 to ~13.3% in 2023, showing gradual uptake but remaining a minority. arXiv
- “Data Issues in Industrial AI Systems: A Meta-Review” (Li et al., 2024)
- Summary: Identifies 72 data lifecycle issues (integration, quality, access) that slow AI adoption in industrial/manufacturing settings. arXiv
Over the past few years, the data has become impossible to ignore. From Auburn University’s Smart Manufacturing Adoption Studies in 2023 and 2024 to Deloitte’s 2025 Smart Manufacturing and Operations Survey, and the findings from SAP, Epicor, and NBS, every report tells the same story: manufacturers and wholesale distributors are lagging behind the rest of the economy in adopting modern technology.
In the 2024 Smart Manufacturing Adoption Study by Auburn University’s ICAMS, researchers found that most small and medium-sized manufacturers are still in the earliest stages of adopting automation, analytics, or artificial intelligence. The prior year’s study painted an equally concerning picture, showing that while large companies were making strides toward Industry 4.0, the majority of smaller operations were struggling to move beyond pilot programs. Deloitte’s 2025 Smart Manufacturing and Operations Survey echoed this, noting that legacy systems, workforce skills, and culture are among the biggest barriers slowing down progress, even for companies that recognize the urgency of transformation.
It’s not just manufacturers. The same challenges ripple across the wholesale distribution sector. A 2023 report titled Driving Growth for Midsize Wholesale Distributors by NBS found that over 60% of distributors admitted they needed to accelerate digital transformation efforts but felt blocked by aging systems and fragmented processes. Similarly, SAP’s 2024 global research Wholesalers Look to Analytics and AI for Growth revealed that many distribution firms are aware of the opportunities analytics could unlock — yet cite lack of integration and poor data visibility as their top hurdles. Epicor’s 2025 industry insights, Practical Ways AI Is Transforming Wholesale Distribution, struck a hopeful note, finding that 83% of distribution executives had adopted AI in at least one function — but most only began within the last two years. In other words, the transformation is happening, but very late and very unevenly.
Academic and market research reinforces the same conclusion. A 2024 study published in ScienceDirect by Faiz and colleagues found that small and medium-sized enterprises — the backbone of the manufacturing economy — consistently adopt digital technologies more slowly than larger firms, citing cost, risk, and limited expertise as persistent constraints. Another study, Research on the Impact of Digital Transformation in Manufacturing Enterprises by Wang et al. (2024), confirmed that while digitization improves efficiency and competitiveness, most manufacturers remain far from full adoption. Even in the AI space, the story is similar: Abdelaal et al. (2024) found that AI adoption in manufacturing rose from 6% in 2020 to only about 13% in 2023 — a gain, yes, but still a small minority.
And if technology adoption feels slow, the reasons are painfully familiar. The Data Issues in Industrial AI Systems review by Li et al. (2024) catalogued more than seventy data-related challenges that manufacturers face — from system integration to data quality and access. These obstacles don’t just make digital transformation slower; they make it intimidating. Many manufacturing leaders grew up in an era where ERP meant “set it and forget it.” But the new digital landscape — real-time analytics, connected customers, AI-powered forecasting — demands constant evolution.
Across all these studies, one theme emerges clearly: manufacturers and distributors are not resistant to change, but they are trapped by decades of legacy systems, manual workflows, and narrow margins that make large-scale innovation feel risky. The technology gap isn’t a matter of unwillingness — it’s a structural disadvantage. A retail company can swap out its ecommerce platform in six months. A manufacturer with custom production lines, supplier integrations, and compliance layers can’t make that leap so easily.
Yet this is exactly why the opportunity is so massive. The world is moving quickly toward intelligent, integrated business ecosystems, and manufacturers and distributors sit on the verge of an overdue transformation. The reports all show a consistent pattern: awareness is there, investment is increasing, and early adopters are seeing meaningful results — but the majority are still finding their way.
Built2Buy exists right in that intersection — where awareness meets action, and where the first wave of manufacturers are ready to modernize, simplify, and take control of their digital relationships. The studies all agree: manufacturers know they’re behind, they’re ready to catch up, and those who make the leap first will define the next generation of industrial growth.