By Apoorva Kasam - July 18, 2023 6 Mins Read
AI-driven prediction, automation, and analysis have increasingly benefitted businesses. It allows them to automate many business processes. Moreover, it enhances efficacy and speed, allowing employees to prioritize high-value tasks.
Enterprises must build an AI-ready workforce by setting up an AI-based strategy. It will help employees understand AI’s full potential and embrace its possibilities. Embracing an AI-ready workforce will ensure that employees are well-prepared for the future.
AI empowers businesses to deliver robust experiences to customers. But, they must also revamp the experiences they provide to the employees. As per a recent report by IBM, “IBM Global AI Adoption Index 2022,” 35% of companies use AI in their business, and 42% explore AI. Additionally, 30% of companies say employees save time with AI and automation software and tools.
Here are a few strategies for enterprises to build an AI-ready workforce.
As AI is evolving, businesses deploy it in many ways. Hence, they must clearly understand their business strategy and goals.
These goals and strategies will help them identify the need for AI. The more they know AI’s role, the better they can determine the investments they need to make.
After understanding the need for AI, businesses must consider the skills and capabilities to build a workforce. They must conduct a complete assessment of the existing workforce’s conceptual skills and abilities of AI.
Assessing a skills inventory is essential. It helps businesses understand the current AI skills and gaps to bridge to achieve objectives.
Businesses must assess their existing learning and knowledge offerings. They must check- what the current learning curriculum cover. What approaches and channels to use? What are the skill and capability gaps they need to upskill?
Businesses must create a learning strategy and roadmap. The roadmap must contain methods to upskill the workforce and recruiting strategy.
They must also ensure that they have the skills and capabilities to compete in the future. Workforce upskilling for AI requires a collaborative effort among decision-makers, HR, and the CLO.
Decision-makers must articulate what they need from the workforce on AI skills. They can also plan on teaching and implementing those skills to their teams. CLO can act as coaches and guides as they develop the training programs they need.
ChatGPT and Auto-GPT have become the standard in many organizations. Hence, employees must learn prompts and understand use cases to better understand the technology.
As per a recent report by McKinsey, “The state of AI in 2022—and a half decade in review,” in 2022, 52% of companies reported that more than 5% of their budgets were for AI. 63% expect their investment to increase in the coming three years.
With increasing investments in the coming years, businesses must set adequate budgets for AI training. They must plan how the employees can absorb the AI knowledge.
Self-study and informal learning are on the rise. These online channels allow employees to access the learning they need.
These channels also offer other benefits. It offers skillful instructors and the opportunity to learn and apply the learnings in daily tasks. E-learning platforms offer adequate technical learning integrated into an employee’s daily tasks. They provide many subjects like machine learning and data visualization.
Businesses can emphasize experiential learning to improve learning effectiveness. Experiential learning allows learners to get out of their comfort zone. It provides them with challenging, stimulating new knowledge.
It offers the opportunity to understand better the learning styles that suits them. It enhances team collaboration since they communicate for clarification, feedback, and new insights.
Organizations must foster a growth mindset about AI. They must establish a sense of understanding of what AI can mean to the business. They must also understand how AI can boost careers. It allows employees to seamlessly adopt AI and be open to learning new skills and approaches.
Moreover, businesses must re-assess the team’s structure. It will help them maximize AI investments and upskilling. They must not place AI as the sole domain of experts and data scientists.
A robust team must be multidisciplinary. Businesses must combine employees with technical and business skills. These teams will help build and consume AI solutions that address business issues and priorities.
Non-data scientists must ensure that the team addresses the business problem at hand. They must communicate insights to decision-makers. Technical experts must harness and apply AI’s capabilities and analytics.
Decision-makers must understand the way AI can change decision-making. They must not make decisions based solely on instinct or experience. They must make decisions per insights obtained from data and algorithms.
They might find the insights varying or counterintuitive. It does not mean that businesses must rely on machines. Instead, they must effectively combine AI with human ingenuity to choose appropriate approaches.
Businesses must establish plans to integrate AI into their operations. The plan must comprise timelines, required resources, and training or upskilling initiatives.
They can also run pilot projects in smaller groups. It allows them to test the AI’s effectiveness and employee responses to the AI solutions before implementing them.
Businesses must help them identify ways to use AI in their roles to support the workforce’s AI adoption. They can achieve it by establishing an organizational change management (OCM) culture.
Businesses must cut down on resistance to using and experimenting with AI tools. They must promote collaboration between AI tools and users of various skill levels.
Establishing an AI-ready workforce via upskilling and re-skilling is vital to thrive in an AI-driven world. Businesses must focus on augmentation, not substitution. This way, they can empower employees to use AI to improve their capabilities. It leads to a robust work experience.
An AI-driven workforce will add value to the company and facilitate greater employee satisfaction. It minimizes employee churn increasing customer satisfaction.
As businesses prepare their employees for the future, they must also understand and address AI’s complexities. The complexities include governance, security, and ethical considerations.
Addressing these challenges will create an AI-ready workforce. Moreover, it also establishes a solid foundation for AI adoption. It effectively balances innovation and responsibility.
It will also build employees’ trust in the technology. It will give them the confidence to develop the needed skills. The organization can quickly adopt the technology to create a solid culture around AI with the proper training, education, and mentorship.
Apoorva Kasam is a Global News Correspondent with OnDot Media. She has done her master's in Bioinformatics and has 18 months of experience in clinical and preclinical data management. She is a content-writing enthusiast, and this is her first stint writing articles on business technology. She specializes in Blockchain, data governance, and supply chain management. Her ideal and digestible writing style displays the current trends, efficiencies, challenges, and relevant mitigation strategies businesses can look forward to. She is looking forward to exploring more technology insights in-depth.
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