Small, Medium Businesses Chart New Direction with AI, IoT

Did you know? 75% of enterprise IoT projects have moved beyond planning stages and 91% of these projects have met or exceeded expectations.

While big tech names continue to generate AI and IoT buzz, small- and medium-sized businesses are acting as key, overlooked catalysts for this latest phase.

A recent survey on technology in small and medium businesses conducted by leading media publications at Informa Tech, IoT World Today and AI Business, found that 71% of small and medium businesses say that the right technology is a major driver for growth and nearly half of them say technology is even more important than people for growth.

Why now?
There’s more to the story than recognition that small and medium businesses are strong champions of technology. Market conditions have also set the stage for this latest cycle of AI and IoT growth. With numerous off-the-shelf options and scalable cloud services now available, barriers to entry for small and medium businesses are quickly being erased. Often more agile and less apt to find themselves entrenched in legacy systems, companies making less than $50 million in annual revenue are better positioned than larger enterprises to experiment with AI and IoT solutions.

The pace of digital transformation also received an unlikely boost from the pandemic. In the face of supply chain difficulties and labor shortages, technology emerged as a way for companies to ensure business continuity by finding ways to do more with less. Those hard-won lessons from the pandemic now have AI and IoT poised to help companies thrive in the face of current economic headwinds as well.

Today’s current economic climate could mean growth rather than retraction of AI and IoT solutions, as organizations again look to find ways to enhance efficiencies during a period of shrinking resources.

Similar goals anchored to a balanced deployment strategy
This focus on maximizing profits and efficiencies in an increasingly difficult market shows clearly in the recent survey results. Deploying AI and IoT solutions requires capital expenditures, but only 9% of respondents identified return on investment as the primary goal. Instead, businesses are looking to new technologies to increase revenue (24% of those surveyed), improve customer experience (22%) and enhance employee efficiency (19%).

Regardless of investment priority, companies of all sizes show similarities in their AI and IoT deployment strategies. For instance, respondents showed a relatively consistent split when comparing the use of internal resources, external development or a mixture of the two for deploying emerging technology.

38% of organizations have an even mix of internal and external development, 35% rely primarily on internal development and 27% rely on outside resources.

Where investments are headed
ChatGPT and Generative AI are garnering headlines, but the survey found a different focus for investment in 2023.

43% of all companies surveyed identified cybersecurity as their top investment priority.

Businesses plan to channel money into cybersecurity regardless of whether they are planning, developing, piloting or already running an AI or IoT project. Plans for cybersecurity investment remain consistent across all phases of the development cycle. However, the percentage of those focused on cybersecurity jumps even higher for companies ready to expand and scale their AI or IoT projects in 2023, with 75% of these saying they will invest in cybersecurity initiatives over the next 12 months.

The survey did, however, identify significant differences between North American and European businesses when comparing plans to invest in cybersecurity. More than (56%) of businesses in North America named cybersecurity as a key investment area, compared to 29% of European enterprises.

Speed bumps remain and vary depending on company size and region
Although small and medium businesses can often be more agile in their approach to new technology adoption, finding executive support for these initiatives appears to be easier at larger companies, with nearly 60% of respondents noting efforts at larger organizations are championed at the highest levels of senior management. At smaller companies, this type of high-level support was noted by 49% of businesses.

le today’s economic headwinds might have complicated finding budget for emerging technologies, lack of in-house talent, complexity of integration and lack of strategy also present challenges for those interested in adopting AI or IoT solutions. Here too, the survey found key differences between smaller and larger companies.

Top barriers to adoption by company size

Smaller companies (less than $50 million a year)

• Lack of talent (40%)
• Inadequate budget (40%)
• Complexity of integration (38%)

Larger companies ($50 million to $1 billion a year)

• Lack of strategy (37%)
• Complexity of integration (32%)
• Lack of talent (32%)

The race for in-house AI and IoT talent appears particularly acute for small and medium businesses in North America, where it was ranked as the top barrier to adoption. European respondents, in contrast, listed lack of talent as their sixth most-pressing concern (lack of budget topped the list of concerns for those in Europe).

No one-size fits all solution
AI and IoT are here to stay and growing rapidly, but there is not a unified story when comparing strategies, investment priorities., and barriers to adoption between smaller and larger companies.

Small and medium businesses looking to invest in new technology and find creative ways to use AI and IoT should look not just to large organizations for a roadmap but rather to each other.

Innovative technologies require innovative strategies to incorporate them into everyday business, and small and e-medium businesses appear to be charting their own unique path forward.

Interested in learning more about how companies are driving adoption of emerging technologies like AI and IoT? Access the full survey results and report to dig deeper into investment priorities, challenges and key differences across regions.