CXOToday has engaged in an exclusive interview with Brett Barton, Global AI Practice Leader, Unisys
How does Unisys’ research reconcile the potential for AI-driven job displacement with its ability to create new roles and enhance existing ones?
Recent research from Unisys shows that 61% of employees feel AI will create more job opportunities, suggesting that, rather than replacing jobs, AI is facilitating the evolution of the workforce. By automating routine tasks, AI is helping employees accomplish more in less time, freeing them up for more strategic and innovative work. 71% of respondents report increased job fulfillment as they spend more time on high-value contributions.
As employees develop AI skills, 79% see the potential for accelerated career progression. Additionally, 44% of the workforce said time saved through AI automation is being redirected into training and personal growth. This is particularly important as AI continues to transform industries and job functions. Upskilling in AI equips workers with in-demand knowledge and positions them for career advancement.
Leaders also recognize AI’s potential for competitive advantage, with 30% citing it as a differentiator, underscoring its value beyond mere efficiency. Of those surveyed, 93% of leaders consider AI essential for future strategies, highlighting that strategic investment in AI enhances productivity and reshapes career pathways, creating a future where technology and talent collaborate.
What are the most common obstacles organizations encounter when integrating AI into their operations? How can companies effectively address these challenges to maximize the benefits of AI adoption?
Some of the biggest challenges companies face when implementing AI in their workplaces include accounting for limited knowledge and resources. Over two-thirds of employees surveyed (69%) say that their companies do not have enough people with the necessary skills and experience to utilize AI effectively; this notion is even more pronounced among executives, with 75% agreeing.
AI integration also faces more tactical challenges, such as data quality, as inconsistent or biased data can impair model accuracy. Existing IT infrastructure may create issues with compatibility.
The shortage of skilled workers available to manage AI systems exacerbates both issues. Organizations must invest in robust data governance to overcome these challenges and prioritize hiring and upskilling talent with AI expertise. Communicating AI’s benefits to stakeholders and implementing targeted training can further foster acceptance, ensuring AI adoption aligns with broader organizational goals.
As AI becomes increasingly sophisticated, what ethical considerations should organizations prioritize to ensure responsible and equitable AI usage?
Organizations deploying AI must prioritize several ethical considerations to ensure responsible and equitable usage. Transparency is critical, especially in highly regulated industries like finance and healthcare, where decisions must be traceable to their origin. Businesses should focus on creating reproducible and consistent models, integrating testing into their development processes to meet these expectations.
Consumer protection is another priority, as fears of losing control to automated systems and the potential for biased or discriminatory decisions necessitate human oversight in AI decision-making. Globally, regulators are emphasizing the ethical use of AI, with some regions requiring human checks to ensure fairness and mitigate bias. Organizations can address these concerns by framing AI as a tool to augment human decisions, embedding ethical principles into their development processes, and employing Chief Ethics Officers to align AI applications with societal values.
Lastly, data privacy and protection remain fundamental. With diverse global regulations, such as GDPR in Europe and the Personal Information Protection Law in China, organizations must adopt flexible, jurisdiction-spanning approaches. Using synthetic data presents a promising solution to address privacy concerns while ensuring unbiased and comprehensive model training. Through continuous monitoring, testing and adherence to ethical guidelines, self-regulation allows companies to innovate responsibly while adapting to evolving regulatory landscapes.
What key metrics can organizations use to assess the impact of AI on their business performance and employee productivity? How can companies effectively track and quantify the return on their AI investments?
To assess AI’s impact on business performance and employee productivity, organizations should focus on a few key metrics directly related to AI’s contributions. Cost savings are among the most significant metrics, as AI can streamline operations by automating repetitive tasks and optimizing processes. This, in turn, reduces operational costs, especially in areas like customer service and supply chain management. Another important metric is revenue growth, as AI enables businesses to adapt more effectively to market changes and customer preferences, potentially leading to increased sales.
Organizations should also track return on investment (ROI), which involves comparing the costs of AI implementation with the financial benefits it generates. This includes not only direct financial gains but also improvements in areas such as efficiency and innovation. In terms of employee productivity, time savings is a key metric, as AI frees employees from mundane tasks, allowing them to focus on more strategic initiatives. Employee efficiency and task completion rates can be measured to assess how AI tools help employees accomplish more in less time. These metrics help organizations justify AI investments and ensure the technology aligns with their business goals.
What specific steps can individuals and organizations take to develop the skills and strategies needed to thrive in an AI-powered world? How can companies foster a culture of continuous learning and adaptation to embrace the opportunities presented by AI?
To thrive in an AI-powered world, fostering a continuous learning and adaptation culture is essential. Organizations should prioritize creating a data-driven culture by aligning data strategies with business goals and ensuring data is accessible and actionable. This cultural shift involves democratizing access to AI tools and resources, which fosters innovation and creates a symbiotic relationship between human and machine intelligence.
Another key component of this shift is enhancing data literacy across the organization. Employees must be equipped with the skills to interpret, manipulate and present data effectively. This means making data accessible, translatable and insightful, moving beyond traditional methods to more advanced analytics. Encouraging data literacy helps employees at all levels to make informed decisions and drive business value.
Leadership plays a pivotal role in cultivating an AI-ready culture by promoting continuous learning and adaptability among employees. Encouraging a mindset that embraces AI and its potential benefits can drive organizational growth and innovation. Addressing ethical considerations and aligning AI initiatives with business outcomes are key components. By focusing on these cultural strategies, companies can create an environment where continuous learning, data literacy, and adaptation are ingrained, enabling them to fully embrace the opportunities presented by AI.
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