Not a business leader who doesn’t feel obligated to act in the field of AI – and act fast. However, neither their organizations nor their technology infrastructures are ready to handle this increase in power.
A an investigation a survey of 7,985 business leaders published by Cisco revealed that 98% of them say it is increasingly urgent to act on AI. Above all, 85% believe they have less than 18 months to do so. But more than half of them (59%) think they are only 12 months old.
At this stage, however, only 13% of companies say they are fully ready to use the potential of AI. This figure was 14% last year. for what Because they are missing:
- Qualified staff
- Higher capacity infrastructure
- AI-ready data
Doubts about AI’s ability to produce results are also on the list.
“Investments in AI have not yet yielded the expected returns”
In short, while 50% of respondents cited pressure from the CEO and their management team, enthusiasm about the transformative power of AI has waned somewhat at this level.
“A large number of people indicate that their investments in AI have not yet yielded the expected gains,” the study’s authors say.
Nearly 50 percent of respondents said they saw no or lower-than-expected gains in areas such as maintaining, expanding, or automating a process or operation.
The big question about processes
The findings highlight that while businesses are eager to adopt and implement AI, their capacity and willingness to take full advantage of it remains limited.
The lack of visible results can also be due to organizations not having the right processes in place to accurately measure the impact of AI. Just over a third (38%) of respondents say they have clearly defined metrics for this.
Still, money continues to flow into AI technologies and projects. At least 50% of respondents say 10-30% of their current IT budget is dedicated to AI.
Talents that are lacking and hard to recruit
But AI skills are a major concern for companies looking to move forward with AI.
- Only 31% of organizations say their talent is well prepared
- 24% say their organization lacks internal talent resources
This shortage has another unintended consequence. Increasing competition for skilled talent is driving up costs, cited by 48% of respondents as a top challenge.
- About 54% of them allocate more budget to hiring new talent
- 40% say their company invests in upskilling and retraining employees
In addition, 51 percent of respondents said they use external providers to train their staff, compared to 39 percent who said they have in-house training programs.
Where are the GPUs?
Infrastructure readiness – or lack thereof – for AI is another area of ​​concern.
Only 21% of companies say they have the necessary GPUs. Only 30% have the capabilities to protect data in AI models with:
- End-to-end encryption
- Security audits
- Continuous monitoring
- Immediate response to threats
“The low levels of infrastructure readiness are troubling, especially considering that 93% of respondents expect their organization’s infrastructure workload to increase with the deployment of AI-based technologies,” the report’s authors emphasize. At the same time, 54% admit that their infrastructure has limited or moderate scalability and flexibility to meet these growing needs.
Inconsistencies or omissions in data preprocessing and cleaning
Additionally, only a third (32%) of respondents say they are ready for data to fully adapt, implement and use AI technologies.
Most companies (80%) report inconsistencies or gaps in data preprocessing and cleaning for AI projects. This figure is almost as high as a year ago (81%). In addition, 64% of them believe that it is possible to improve the traceability of data.
Measuring the impact of AI on growth and revenue is another area of ​​concern. While 87% of executives say their company has a process in place to measure the impact of AI, only 38% have clearly defined metrics. In terms of financial readiness, 81% (up from 84% last year) have a financial strategy to support AI implementation. But only 43% say they have a long-term financial plan.
4 recommendations for catching up with AI in business
The report’s authors make the following recommendations for organizations and technologies to keep up with the growing demands for AI:
Invest in scalable, adaptable and secure infrastructure
Scalability and security are the keywords for successful AI planning.
“As generative AI tools become more available, businesses need to put technologies and policies in place to ensure they protect against unauthorized data sharing and loss and are able to defend against rapid injection, data and model poisoning, and other AI-specific attacks.”
Improve data management, integration and management
Organizations need to address two key areas: data quality and governance.
“Implement comprehensive governance frameworks to ensure data flows across the organization as required comply with relevant regulations.”
Focus on developing and retaining talent
“The buzz around AI is creating a shortage of talent with the right skill set and driving up the cost of hiring.”
The authors strongly recommend investing in existing talent pools.
“These include creating continuing education opportunities for staff, encouraging cross-functional teams to collaborate and share knowledge on AI projects and, most importantly, looking for skills that can be transferred from an existing role to an AI-driven role , in order to expand the available talent pool.”
Foster a favorable organizational culture and vision for AI
Periodically review and reevaluate the AI ​​strategy to ensure it aligns with the company’s overall business goals.
Additionally, “organizations must ensure that as they adopt and implement AI in their business areas, they not only highlight the potential benefits, but also consider the concerns employees may have about the impact on their work and role.”
Encourage employees to “push the boundaries and contribute to the company’s AI goals to ensure sustainable growth and competitive advantage.”
