Midmarket Businesses Face Challenges Implementing AI

A new survey from RSM US LLP, a provider of assurance, tax and consulting services for the middle market, shows most middle market organizations are adopting AI (78%) and generative AI (77%). However, 54% of those using generative AI find its deployment more challenging than anticipated.

A strong majority (89%) of executive respondents to the survey — which targeted businesses with annual revenues of $10 million to $1 billion — report their organizations plan to boost their budgets around AI technologies and nearly three quarters of respondents (74%) are focusing their dollars squarely on generative AI. The top goals for generative AI use include improved quality control (58%), enhanced customer service (51%), automation of repetitive tasks (45%) and increased employee productivity and creativity (45%).

“AI and generative AI are making significant impacts to our industry — perhaps more than any previous technology,” said Sergio de la Fe, enterprise digital leader and partner with RSM US LLP. “Our survey underscores the necessity for middle market organizations to develop a comprehensive AI strategy that encompasses the entire value chain. Considering the complexity of AI technologies, it’s no surprise that roughly two-thirds (67%) of middle market leaders surveyed recognize the need for external assistance to fully capitalize on the advantages of their selected AI solutions.”

Interestingly, among those respondents whose businesses plan to refrain from generative AI use for now, 46% cite concerns around data security, 44% note perceived difficulty with operational integration and 39% report a lack of understanding or knowledge about generative AI tools.

Other key findings from RSM’s middle market AI technology research include:

85% completely agree/somewhat agree that generative AI has impacted their organization more positively than expected.
77% report using generative AI solutions such as ChatGPT (82%), Microsoft Copilot (30%) and Adobe Firefly (24%).
74% have a budget dedicated to generative AI investments and 89% plan to increase their budget next fiscal year.
41% report being in the partial implementation phase for AI and 34% among those using generative AI.

Implementing and scaling AI technologies comes with a variety of challenges the middle market needs to navigate. These can include:

Data quality: Organizations must prioritize data quality management, ensuring accuracy and completeness through processes such as data cleansing and enrichment, supplemented by external data when required.
Skills gap: A lack of overall AI expertise within an organization can hinder the adoption process so investing in training is crucial to empower employees, accelerate implementation and drive business innovation.
Integration with existing systems: Incorporating generative AI solutions into existing processes and systems, like CRM or ERP, can pose complexity and requires detailed planning to guarantee seamless integration with the current infrastructure.
Ethical and legal considerations: Organizations must tackle AI-related issues by creating standards to ensure system transparency and accountability, and perform routine audits to prevent ethical, legal, regulatory or compliance risks.
Cost: The investment in hardware, software and personnel can be notable for the middle market so organizations need to consider the benefits such as increased efficiency, improved decision making and cost savings, against the expenses involved in its adoption.