Artificial intelligence is setting the corporate stage. Is your company ready for the shift?
AI's influence in today's business landscape is undeniable, but it raises a crucial question: are businesses truly prepped for this technological shift? Deploying AI and machine learning can instigate significant changes, potentially introducing risk. Here's the skinny on what leaders in technology and finance should know.
"Many organizations recognize the transformative power of AI, yet executives and employees may struggle to prepare for its integration," says Rajprasath Subramanian, principal enterprise architect at business and technology innovation at SAP. This struggle often stems from a lack of understanding about AI capabilities, particularly in rapidly advancing areas like autonomous AI and swanky language models, he notes.
Moreover, job displacement fears due to AI adoption can lead to reluctance or apprehension among employees. Subramanian points out that this worry can hinder constructive interaction with AI tools, restricting golden opportunities for upskilling.
According to Subramanian, it's crucial to stay abreast of AI's lightning-fast evolution as organizations frequently struggle to keep up and avoid potential skills gaps.
A study by IT and business services firm Accenture surveyed 6,450 C-suite leaders and 6,000 non-C-suite employees and found that both groups expect business changes to occur at a breakneck pace in 2025. Alarmingly, they feel less prepared for these changes than they did the year prior.
Half of C-suite leaders stated that their companies are underprepared, and after a year of rampant generative AI adoption, only 36% said their organizations were fully prepped for tech disruption.
"Most companies lack a unified AI foundation, making it difficult to balance speed with required controls," said Lan Guan, chief AI officer at Accenture.
One-third of the C-suite execs surveyed by Accenture mentioned limitations with data or tech infrastructure as the primary obstacle to implementing and scaling generative AI. "Many CIOs are still hesitant to scale new AI tools due to uncertain costs and the constant barrage of new advancements," Guan added.
Companies need to tailor AI to their exclusive data rather than rely on off-the-shelf solutions for maximum benefit, Guan stated. However, finding easy ways to merge AI with their specialized data remains a struggle for many companies.
When asked about the reasons for lack of preparedness and factors that boost an organization's ability to squeeze the most value from AI, Guan said it all comes down to the investment strategy and implementation process.
Generative AI is projected to boost productivity by over 20% in the next three years, so being unprepared means missed opportunities for significant ROI on AI investments and possibly lagging behind industry competitors, Guan emphasized.
In addition, an unskilled workforce may grapple with adapting to new workflows, leading to productivity disruption during the transition phase. "Without proper education and skill-upgrade initiatives, employees might yield suboptimal AI tool performance and miss out on opportunities for efficiency gains," Subramanian warns.
Another concern is the impact on employee morale and retention. "Fear about AI's impact on job roles can lead to diminished employee morale, engagement, and increased turnover rates," Subramanian points out.
To help organizations brace for AI's broader use, Subramanian suggests several steps:
- Collaborate with other C-suite executives to formulate a comprehensive AI strategy that aligns with the organization's overall vision and mission.
- Invest in employee training and skill-upgrade initiatives to bridge the skills gap. Companies like Johnson & Johnson have made mandatory generative AI training available to over 56,000 employees.
- Establish a strong data governance system that ensures data, security, and regulatory compliance.
- Foster an IT infrastructure capable of processing large amounts of data.
By proactively addressing these aspects, companies can facilitate a smoother transition into AI adoption, enabling them to fully harness the benefits of AI technologies.
- Rajprasath Subramanian, an expert in technology and finance, indicates that many organizations grapple with preparing for AI integration due to a lack of understanding about its advanced capabilities.
- Subramanian also notes that fear of job displacement among employees can hinder constructive interaction with AI tools, restricting opportunities for upskilling.
- Lan Guan, chief AI officer at Accenture, highlights that most companies struggle to keep up with AI's rapid evolution, often leading to potential skills gaps.
- A study by Accenture found that both C-suite leaders and non-C-suite employees expect business changes to occur quickly in 2025, but feel less prepared for these changes than they did the previous year.
- According to the study, half of the C-suite leaders stated that their companies are underprepared, and only 36% of them said their organizations were fully prepared for tech disruption.
- Guan notes that companies lack a unified AI foundation, making it difficult to balance speed with required controls.
- One-third of the C-suite execs surveyed by Accenture mentioned limitations with data or tech infrastructure as the primary obstacle to implementing and scaling generative AI.
- Guan suggests that companies need to tailor AI to their exclusive data for maximum benefit, but finding easy ways to merge AI with their specialized data remains a struggle for many organizations.
- To brace for AI's broader use, Subramanian recommends collaborating with other C-suite executives, investing in employee training, establishing a strong data governance system, and fostering an IT infrastructure capable of processing large amounts of data. By addressing these aspects, companies can facilitate a smoother transition into AI adoption, enabling them to fully harness the benefits of AI technologies.
