25
AI &AUTOMATION BAROMETER REPORT
What challenges are you facing, or did you face, with implementation?
Company-wide dilemma
• Enterprise governance and security slows down departmental experimentation. A choice of AI
technology from the organization means we may not be able to use other competing technologies.
• Getting approval to experiment
• Finding ideas for what works the best for our company
• Identifying best applications for client services, as opposed to internal use, and how to present that
• Many AI solutions offerred. Not enough to check and select.
• Proof of concept
• Uncertainty of relevancy
• Understanding exactly what can be done with AI and what can be really useful
• Wrap our heads around on where to start and the long term implications/ROI aspects related to it.
• Fast speed of changes in technology
Technical or quality issues
• Defining the criteria of usability of AI outputs in terms of quality and ethical concerns.
• Delays in availability of updated models that would produce higher levels of customization.
Challenges
Organizations with an annual revenue of USD $1-5M found that integrating AI in their tech
infrastructure was not seamless when compared to those at larger organizations. Regionally, those
based in Europe had the most difficulties integrating AI, whereas for North Americans the positive
seemed to outweigh the negative.
How seamlessly have you integrated AI in your current
tech infrastructure?
Seamlessly Neutral Not Seamlessly Not applicable
10% 38% 28% 24%
AI &AUTOMATION BAROMETER REPORT
What challenges are you facing, or did you face, with implementation?
Company-wide dilemma
• Enterprise governance and security slows down departmental experimentation. A choice of AI
technology from the organization means we may not be able to use other competing technologies.
• Getting approval to experiment
• Finding ideas for what works the best for our company
• Identifying best applications for client services, as opposed to internal use, and how to present that
• Many AI solutions offerred. Not enough to check and select.
• Proof of concept
• Uncertainty of relevancy
• Understanding exactly what can be done with AI and what can be really useful
• Wrap our heads around on where to start and the long term implications/ROI aspects related to it.
• Fast speed of changes in technology
Technical or quality issues
• Defining the criteria of usability of AI outputs in terms of quality and ethical concerns.
• Delays in availability of updated models that would produce higher levels of customization.
Challenges
Organizations with an annual revenue of USD $1-5M found that integrating AI in their tech
infrastructure was not seamless when compared to those at larger organizations. Regionally, those
based in Europe had the most difficulties integrating AI, whereas for North Americans the positive
seemed to outweigh the negative.
How seamlessly have you integrated AI in your current
tech infrastructure?
Seamlessly Neutral Not Seamlessly Not applicable
10% 38% 28% 24%
