Dive Brief:

• The number of companies with AI budgets in the $500,000 to $5 million range rose 55% year over year, according to Appen's State of AI and Machine Learning report released Tuesday. The survey was conducted by The Harris Poll on behalf of Appen and consulted 501 business leaders and data specialists.

• Scaling AI technology is a bigger priority for enterprise businesses when compared to their smaller counterparts. By contrast, diversity of the data powering AI is a higher priority for small and medium companies than for enterprises.

• Regardless of size, businesses with annual AI budgets of $1 million or more were more likely to bring their projects closer to deployment. The majority of businesses said the COVID-19 pandemic accelerated ongoing projects.

Dive Insight:

Companies used AI to respond to massive change during the pandemic, allowing organizations of all sizes to grasp its value. Now, the challenge is setting up for the next stage of AI deployment.

In the next phase, challenges include internal alignment around technology deployment, according to Sid Mistry, VP of marketing at Appen.

"Where we're seeing people kind of get hung up is: What's the use case?" said Mistry. Rather than getting stuck on whether a problem can be solved by computer vision or a chatbot, organizations can focus on "whatever the enterprise's issue is that needs data to help solve and optimize the process."

With technology response tactics in place, the next task for business leaders is crystallizing the initiatives they put in place last year. Companies can benefit from unifying their approach, going from separate initiatives in areas such as AI, 5G or Internet of Things, to a more cohesive strategy on emerging technologies.

The disconnect between the way enterprises and smaller businesses prioritize scale or diversity of the data reflects an evolution on the part of larger enterprises, while younger organizations might still be catching up in terms of technology maturity, said Mistry.

Across organizations, AI capabilities play a role in the COVID-19 recovery phase, as two-thirds of senior executives plan to increase investment in automation and AI, a report from McKinsey found.

Regardless of company size or budget scope, failing to grasp the ethical dimensions of AI can lead to sunken resources, according to Rahul Singhal, chief product officer at Innodata.

"We’re seeing that businesses are often starting off on the wrong foot by focusing first on scale," Singhal said. "We’ve found that if a company deprioritizes the importance of having high-quality, diverse data at the start, a lot of time and money is wasted on their project."