Visions of the Future: How Computer Vision Technology is Transforming Industries

Productivity expectations are high.

On average, respondents anticipate a productivity increase of 42%, rising to 52% in manufacturing and dropping to 32% in location-based entertainment.

These variations are likely related to its use cases in each sector – while manufacturing applications are likely to increase the quantity of output organisations can deliver, in locationbased entertainment the focus is much more on the quality of user experiences; providing better experiences rather than more of them.

Computer Vision technology is used across a wide variety of business departments and applications.

Practical activities such as repairs and maintenance, production line monitoring, and Practical activities such as repairs and maintenance, production line monitoring, and quality control slightly outweigh use in security and health and safety. control slightly outweigh use in security and health and safety.

Applications in logistics and supply chain are popular, along with real-time projection mapping and people tracking, demonstrating the broad scope of use cases relevant to Computer Vision technology.

Practical barriers relate to support, knowledge, and implementation costs.

Installing new technologies is only the first step. Organisations report that they are struggling to find third-party support.

High demand for skills in new technology areas often results in battles for talent, with companies struggling to retain knowledge within the business as employees are tempted by high salaries elsewhere. High costs are always a consideration, too, especially for early adopters, and our research bears this out.

Ethical concerns show organisations are aware of AI’s moral maze.

Data security, privacy, a lack of corporate guidance, and fears of job displacement are all key concerns for professionals already deploying AI. They show awareness of the ethical issues relating to different AI use cases, demonstrating that these form part of decision-making around implementation.

As companies attempt to find a balance between the business advantages of AI and its impact on their workforce and wider society, this awareness should evolve into practical strategies to support effective but sensitive AI deployments.

AI professionals are enthusiastic about GenAI and adoption is rapid.

68% of respondents say generative AI is important to their organisation and more than a third have already implemented solutions and are seeing benefits.

Experts who have already overseen the implementation of computer vision in their organisation should be in a strong position to introduce generative AI and identify where AIs can co-operate to enhance and automate processes.

Methodology:

The research was conducted by independent research company, Opinion Matters, among 300 senior decision makers responsible for digital transformation and AI/ computer vision implementation working in companies with an annual turnover of 50 million+ Euros across Germany and the UK.