The AI Moment for the Midsize Market Has Arrived

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Data Society         
machine learning
  October 2022                
machine learning         Blog
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For the decades since the data revolution began a transformative trek across industries, ​​large enterprises and multinational corporations have made impressive gains by harnessing data’s considerable power. Still, while these large companies have had the advantage of leveraging their abundant resources toward adopting data science technologies, the widely touted benefits of data innovations have remained elusive to many midsize businesses. The significant investment necessary for implementing data science technologies is just one of several hurdles that have kept data transformation out of reach for many players outside the multinational sphere. However, companies that have thus far been left behind should take heart. Following the historical pattern of innovation’s spread, the midsize market is now poised to take its place in the ranks of data-driven companies. These technologies, most notably AI-enabled tools, are rapidly becoming essential to remaining competitive and thriving.

The Midsize Market’s AI Challenges: The Distribution of Enterprise AI Adoption

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First, here’s a bit about data science and AI adoption. As with most technological innovations, data science once resided only in the realm of a limited scientific circle before reaching into the world of engineers who had access to bountiful resources through multinational titans. Meanwhile, the midsize market has lagged in reaping data science’s benefits, with only one-quarter of midsize companies reporting in 2021 that they used or planned to use AI in the next year, compared to nearly half of large companies. This disparity has broader implications for the national economy in the form of a productivity gap between the largest companies and their smaller counterparts. 

There are typically several barriers to AI adoption, such as:

  • Limited resources to invest in technology infrastructure.
  • Limited in-house expertise.
  • Lack of strategy.
  • Lack of leadership buy-in.

These obstacles may explain the delay in the midsize market’s AI transformation.

Opening Pathways to the Midsize Market’s AI-Driven Future

Fortunately, data science technology has followed the typical trajectory of innovation and has become more widely accessible. In addition, trends such as widespread adoption of enterprise open-source software, increased availability of SaaS, and the rapid spread of data-driven devices introducing new data sources provide new opportunities for more businesses to embrace AI. Therefore, the moment has arrived for the midsize market to join the industry’s behemoth pioneers on the path toward increased digitization and data maturity. 

“There is no business that can’t get value from this,” says Laurie McCabe, co-founder and partner of SMB Group, Inc., “Every SMB should understand that the efficiency and insight that AI brings can be a huge differentiator for their business.” Moreover, the midsize market needs no further persuasion, with 80% of midsize companies planning to increase their annual AI investment, compared to 57% of large companies, according to a 2021 Deloitte survey. 

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These numbers strongly suggest that many enterprises outside the multinational tier are eager to take advantage of AI’s power to drive business benefits. Among the wealth of AI-driven tools that the midsize market is ripe to embrace are chatbots to facilitate customer service interactions and analytics to inform supply chain management. Other advantages these companies can gain from AI adoption include:

  • Increased organizational efficiency through enhanced business management, improved company processes, resource optimization, and automation of routine tasks.
  • Enhanced ability to gather insights by leveraging IoT effectively. 
  • More vital supply chain management.
  • More targeted marketing and improved go-to-market strategy.
  • Tighter security. 
  • Improved customer service through increased capacity to predict customer behavior and provide more personalized customer experiences.
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Knocking Down the Final Obstacles to AI Adoption in the Midsize Market

While these technologies have been moving closer to the midsize market’s reach each day, challenges remain, such as:

  • Cultivating the in-house skills to implement new technologies.
  • Achieving the necessary level of organizational data maturity.
  • Building a solid data strategy and infrastructure.

To overcome these hurdles, midsize and large companies must invest in upskilling and reskilling their teams with comprehensive data science training for all roles and levels. A subject-matter expert like Data Society can provide an understanding of available data, facilitate the rapid deployment of an upskilling platform, and deliver the training the midsize market’s workforce will need for a successful initiation into the world of data-driven enterprise.


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Data Society provides customized, industry-tailored data science training solutions—partnering with organizations to educate, equip, and empower their workforce with the skills to achieve their goals and expand their impact.

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