Upskilling for AI and Machine Learning: Lessons from Google

AI and machine learning

Businesses are at a crossroad with the growing impacts of machine learning and artificial intelligence. Companies need to retrain their workforce to ensure longevity and profitability.

The AI collaboration between machines and humans is enhancing customer experiences. It is also helping to create new job roles. AI upskilling can help build a winning business culture, as highlighted by Google’s prowess in AI.

AI Disruption to the Way We Work

AI is disrupting the world of work. There is a growing digital skills gap in the AI and ML sectors, and data shows that 50% of the current job roles will change due to AI automation in the next decade. On top of that, 90% of all jobs will go to digital-savvy employees.

AI automation will disrupt wages, the world economy, and over 1.2 billion employees worldwide. It may eliminate some job roles, but will also create fresh ones. To illustrate this point, machine learning algorithms may replace 75 million work tasks and yield over 133 million new positions for the upskilled worker.

While AI could displace about 7 million jobs in the UK alone in the next decade, it will create 7.2 million new jobs. Consequently, workers urgently need to upskill or reskill to adapt to the ongoing changes. To this end, business managers should implement an AI upskilling program for their organisations.

Benefits of AI Upskilling for Businesses

AI upskilling builds future-ready businesses and employees. It is a deliberate and significant investment in knowledge, capabilities, and skills that makes organisations ready to consume and build AI technology tools and insights.

Furthermore, almost every business will, in the future, become an AI business in some way. Targeted upskilling initiatives can build AI literacy and help your organisation to kick off its AI solutions-building processes and enjoy a higher return on investment.

Additionally, organisations that offer reskilling and upskilling programs have more profit margins, provide higher income, and have a high 70% employee retention rate.

To illustrate the benefits of an organisation-wide AI upskilling initiative, Forrester Research recently described Google Cloud as the undisputed leader in unified data and artificial intelligence (AI) innovation and architecture.

The Q4 2021, The Forrester Wave™: AI Infrastructure report gives the cloud computing service suite the highest possible evaluation score in the Forrester Wave criteria.

The assessment formula considers factors such as Google’s AI infrastructure innovation and easy-to-deploy enterprise-level machine learning (ML) models. The research and advisory company report also lauds Google Cloud’s data protection security systems and its vast partner ecosystem.

It says that businesses that leverage Google Cloud will have access to the most innovative AI, machine, and deep learning infrastructure globally. This excellent business review for Google will bring onboard more partnerships.

Google AI Upskilling Success Story

Google has made big bets in the AI sector, making it the focal point of its future. The multinational technology company has set aside billions of dollars to embed AI and ML into its disparate divisions. However, Google’s wins in the AI sector result from years of intentional devotion to the upskilling and reskilling of its employees.

As an illustration, in its formative years, Google would hire all top students in AI from institutions of higher learning. However, when the company underwent a massive expansion, most workstations remained unfilled because academic programs would barely produce adequate ML experts.

Fortunately, it embraced the challenge of making its engineering workforce familiar or adept at ML by rebranding to a machine learning first organisation. So, in the place of the relentless hire of top AI experts, John Giannandrea, its former search and AI chief took up machine learning evangelism as part of his role.

So, kicked off Google’s famous smart retraining program that blew up its machine learning expert numbers amongst its software engineers. It, for instance, rolled out the Machine Learning Ninja Program, which would pool together a team of coders to an AI techniques learning program.

This upskilling initiative would introduce computer scientists to learning algorithms and deep learning specialists, expanding the ML and AI elite within Google’s walls.

Google’s ninja program brought about a cognitive shift in its HR operations. In 2016, for instance, only 10% of its 25,000 engineers were proficient in machine learning. Its AI reskilling long-term plan would later raise an army of ML specialists and a majority of machine learning adept engineers.

How to Create an Effective AI Training Program

AI course online

1. Align your AI strategy with your organisation’s goal

To ensure the success of AI training programs, managers should adopt data-driven strategies to ensure that all reskilling and upskilling efforts eventually bring a return on investment. To illustrate this point, when AT&T data showed that 50% of its employees lacked the STEM skills it would need in the future, it kicked off a massive reskilling initiative.

They collaborate with various online educational platforms via a career portal. Besides offering a personalised learning experience, the portal provides data that helps employees identify vital skill gaps and plan for their future.

2. Identify skill gaps using data

Study your workforce’s data and seek out any skills gaps. Then, use predictive analytics to identify business areas that benefit from reskilling strategies. Also, you can leverage the Accenture strategy and launch reskilling training via an app.

Accenture’s $1 billion per year Connected Learning Platform blends a digital and classroom experience, giving its employees control of their career and learning development.

3. Tweak your training over time

Analyse and optimise your AI reskilling programs to match your productivity key metrics. Test a variety of training initiatives, such as these AI courses online, and make comparisons between their success rates.

Pivot to Stay Ahead of the AI Upskilling Curve

Most business leaders are aware of the growing digital skills disparity in the workplace, but very few have embraced upskilling initiatives. As per forum data, 45% of business leaders demonstrate an awareness of the coming automation wave.

Unfortunately, only 15% of them communicate about upskilling their task force and organisations in readiness for the coming change. Therefore, the international lobbying organisation warns of a rapidly growing disparity between job roles and workers.

Managers should pivot before time and competition kick them out of the AI race to close the imminent AI skills gap. Doing so will preserve resources through the cost-effective training of workers, leading to higher employee retention rates.

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