Artificial intelligence (AI) is transforming the workplace. As more companies adopt AI technologies like machine learning, natural language processing, and robotics, employees need new skills to work effectively alongside these intelligent machines. Forward-thinking companies are implementing training programs to upskill their workforce for the AI-powered future.
The Rise of AI in Business
AI is moving beyond hype and into practical business applications. According to a 2021 survey by Deloitte, 97% of organizations are already using some form of AI, up from 81% in 2020. The global AI market is projected to grow from $327.5 billion in 2021 to over $554 billion by 2024.
This growth is fueled by AI’s ability to automate tasks, gain insights from data, and enhance products and services. Use cases span all industries and functions:
- Healthcare: AI can analyze medical images to detect diseases earlier and more accurately than humans.
- Manufacturing: Smart robotics can work alongside people on production lines without endangering them.
- Customer service: Chatbots use natural language processing to understand and respond to customer inquiries 24/7.
- Marketing: AI informs campaigns by predicting customer lifetime value and personalizing offers.
- Finance: Algorithms detect fraudulent transactions in real time and model investment risks.
As AI becomes ubiquitous, human workers need to adapt. A 2021 MIT Sloan Management Review survey found that companies implementing AI expect over 70% of their employees will need retraining or upskilling. This training gap presents an opportunity to educate the workforce to capitalize on AI’s benefits.
Preparing the Workforce for an AI Future
How are leading companies tackling AI training? Strategies aim to increase AI literacy, upskill for new roles, and foster human-AI collaboration:
Building AI Literacy
Before working with AI, employees need core knowledge of what it is and how it functions. AI literacy programs cover:
- AI basics – types of AI technologies, capabilities and limitations
- Ethics – risks of bias, security issues, ensuring transparency and accountability
- AI in the business – existing and potential applications, impact on workflows and roles
- AI trends – developments like natural language generation, computer vision, robotics
Training empowers people to ask informed questions, spot opportunities, and evaluate AI vendors and solutions. It also sets expectations – while AI excels at repetitive tasks, workers maintain advantages in areas like communication, problem-solving, creativity and empathy. Education increases trust in AI to encourage adoption.
Upskilling for New Roles
As AI automates mundane work, new specialized roles emerge that complement AI’s capabilities. Companies are upskilling employees to fill these positions through online courses, certification programs, on-the-job training and external hiring. Roles include:
- AI trainers – prepare data, “teach” machine learning models
- AI explainers – interpret model behavior, identify potential biases
- Workflow designers – optimize processes to incorporate AI, human staffers
- Bot managers – develop chatbots, optimize interactions, enhance capabilities over time
- Analyst-programmers – turn business ideas into code, analyze data, refine algorithms
- AI ethicists – ensure models act responsibly and align with human values
Upskilling allows companies to fill critical roles from within, while employees gain marketable skills. The World Economic Forum projects that by 2025, 97 million new AI roles will emerge.
Fostering Human-AI Collaboration
At the cutting edge, companies are training workers to collaborate directly with AI technologies on complex challenges:
- Co-learning through simulations and virtual environments
- Feedback loops to improve systems over time
- Team-building workshops to increase trust
- Collaborative problem-solving on issues like predictive maintenance
- Change management processes to integrate AI-human teams
Research shows collaborative intelligence often outperforms either humans or AI working alone. As AI capabilities grow, training to partner effectively with these technologies will become essential.
AI Training Program Best Practices
How can companies implement successful AI training initiatives? Key elements include:
Securing Executive Buy-In
For training to scale across the organization, leadership must actively sponsor upskilling efforts. Executives can:
- Allocate budget and resources
- Champion the program company-wide
- Incentivize participation through raises, promotions and recognition
- Demonstrate the value of AI and need for human guidance
- Position training as a strategic investment in the workforce
Assessing Skill Gaps
Training should target specific skill gaps rather than take a one-size-fits-all approach. Assessment methods include:
- Surveys to gauge AI proficiency and training needs
- Audits of existing capabilities compared to future requirements
- Benchmarking against competitors and standards
- Role analysis of skills needed for key emerging positions
Assessments should inform training priorities and content across departments, locations and experience levels.
Training content and formats should align with learners’ needs and constraints:
- Job-specific – e.g. data science, engineering, creative roles
- Experience level – introductory vs. advanced content
- Modalities – self-paced e-learning, virtual or in-person instructor-led sessions, on-the-job training, etc.
- Schedule – integrate into workflows versus separate training time
Segmenting audiences allows a targeted approach while delivering scalable training across the organization.
Does it make sense to build and deliver training internally or partner with specialized providers? Factors include:
- Budget – develop in-house for cost savings
- Expertise – leverage external partners for access to top instructors
- Customization – in-house allows tailoring to company culture and systems
- Certifications – partner for recognized programs
- Capacity – use vendor for scalability if training large populations
Many companies blend internal and partnered offerings for the right mix of customization, quality and scale.
Tracking and Improving
Like any business initiative, the impact of training should be measured for continuous improvement:
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- Participation and completion data – monitor program reach and engagement
- Assessments – pre- and post-training to gauge knowledge gains
- Surveys – participant feedback on relevance, quality and applicability
- Observation – changes in on-the-job behavior and performance
- Metrics – e.g. faster AI adoption, better human-AI collaboration
Proactively gather data, review insights with stakeholders, and refine approaches accordingly.
Companies Making the AI Training Investment
Global leaders across sectors are prioritizing upskilling for AI:
The tech giant makes a massive investment in employee skills, spending over $1 billion annually. All employees have access to LinkedIn Learning and Microsoft Learn online training platforms. Amid its AI push, Microsoft launched AI Business School to educate all 153,000 workers on AI applications, ethics and strategy. The company has also formed an AI Academy that identifies candidates for the most in-demand AI roles then trains them through a 16-week bootcamp.
The consulting powerhouse established Deloitte AI Academy to build AI fluency throughout the organization. The program includes AI fundamentals, business applications, hands-on labs using Azure AI tools and ethics. Deloitte also acquires and nurtures talent through partnerships with doctoral programs and immersive virtual reality training for client services staff to learn AI teaming.
The CPG leader has an ambitious plan to upskill its entire 155,000 workforce. partnering with platforms like Coursera, Pluralsight and Udacity to offer thousands of digital courses. This allows employees at all levels to build tech-adjacent skills needed to work with AI-powered analytics, digital marketing, IoT and more. Unilever prioritizes reskilling to limit redundancies as AI automates some jobs.
The investment firm is growing its AI Center of Excellence while upskilling all employees in AI. The Applied AI Academy provides introductory classes on AI concepts and ethics as well as the bank’s AI systems. Advanced courses help technologists build critical skills in data science, machine learning ops and model development. This internal academy scales AI capabilities across the 88,000-person company.
The Future of Work is AI + Human
The message for employees is clear: with AI poised to transform business, the time is now to skill up for the future. Companies that equip their workforces to adopt AI will gain competitive advantage. A shared commitment to continuous learning will ensure people can thrive alongside increasingly intelligent machines. The future workplace will blend AI’s speed and scalability with human judgment, empathy and creativity. Forward-looking training initiatives will pave the way for this hybrid model where humans and AI collaborate to drive productivity, innovation and growth.
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