Reskilling in AI: A Solution to the Workforce Situation

Reskilling in AI: A Solution to the Workforce Situation ...

The World Economic Forum predicts that 97 million new jobs will arise as artificial intelligence (AI) alters the nature of work and influences the new division of labor between humans, machines, and algorithms. In particular, a recent McKinsey survey found that AI technologies might increase to $1 trillion per year. AI is continuing its steady rise and is starting to have a profound impact on the financial services industry, although its potential is still far from fully realized.

The technology that drives AI to be successful in financial services, including risk management, personalization, fraud detection, and ESG analytics. The problem is that worldwide shortage of workers with advanced learning disabilities are limiting their ability to acquire the necessary skills necessary to help them succeed.

Today, 87 percent of employees believe retraining and upskilling options at workplaces are essential, but this time, more companies ranked upskilling their workforce as a top-5 business priority than before the epidemic. However, businesses that do not focus on powering AI training will fall behind in a tight hiring market. Here are a few key tips for prospective employers looking to prioritize reskilling efforts.

Build data literacy with customizable learning paths.

Increasing data literacy across the organization assists line of business and domain experts (Sales, HR, Marketing, Financial Analysts, etc.) collaborate with AI and machine learning experts in order to move beyond proof of concepts and experimentation.

When AI tools are deployed at scale, those employees who work with AI systems must understand how these systems work and what constraints and limitations might be. Reskilling these individuals may include how to interpret the results of AI/ML models or how to intervene with AI/ML experts when the results appear.

A recent McKinsey study found that effective reskilling is 20% more cost-effective than hiring and firing methods, and that employing the appropriate tools and technologies can assist companies accomplish their reskilling goals.

Before taking on AI reskilling initiatives, banks and financial services organizations must first understand the outcome they are achieving and what skills are required. An employee self-assessment survey that focuses on necessary skills may assist organizations determine a customized curriculum and strategy based on existing skills gaps.

The notion of a one-size-fits-all training program or that employees should take considerable time away from the office to attend courses is no longer relevant. Using digital learning platforms like Skillsoft, Udacity, or Udemy, or integrating content into mainstream work systems can help employees learn quickly. Axonify may also provide 5- to 10-minute microlearning sessions to individuals within their daily workflow. Companies may choose to develop their own programs with the help of industry experts and professors who are experts in their field.

Turn to existing in-house equipment and groups for AI reskilling.

According to a Deloitte survey, 94 percent of employees would stay at a company if it was aided them develop and learn new skills, but only 15% of them will have access to learning opportunities directly related to their jobs. AI reskilling provides a tremendous benefit for financial services companies and their employees, but it may be difficult to employ time commitments as a result of the removal of existing companies.

Three excellent sources to assist in accelerating AI/ML training and implementation:

  • Industry consortiums: You might also consider joining industry consortiums that support your teams progress and encourage employee growth through collaborative groups. For example, FINOS (fintech open source consortium under Linux Foundation) helps facilitate the processing and exchange of financial data throughout the entire banking ecosystem.
  • Cloud Service Providers (CSP) Training and Certification Programs: Many of the CSPs, such as AWS, Google Cloud and Microsoft, offer ML training and certification programs for free or subsidized prices. These self-guided programs vary in topics and tracks from understanding conversational AI to machine learning for business and technical decision-makers and are designed for those looking to learn new skills or to build or switch careers.
  • Technology Enablers AI-powered Solution Accelerators: Additionally, many companies like IBM, AWS, PwC and Databricks offer easily deployable tools and solutions accelerators for common data analytics and machine learning use cases that organizations can utilize. Instead of enduring the weeks of development time, technical practitioners like data scientists, solutions architects and developers (from novice to experts) can leverage these accelerators to enable faster time to modernization and help talent upskilling. At Databricks, our financial services solutions accelerators help companies capitalize on the open banking paradigm, providing free code and training that helps with front-to-back-end automation. This includes free SAS to Python training to help technical and non-technical teams combine AI and rules-based fraud algorithms.

Recognize the benefits of providing AI reskilling opportunities in cultural settings.

Investing in employees'' knowledge and skills can help establish a positive business culture and help employees reduce turnover, while increasing employee confidence and productivity, and it help create a more well-rounded workforce.

Financial services organizations may make better progress on their diversity, equity, and inclusion strategies by empowering individuals who have encountered barriers to higher education. To address this and the skills gap, banks including Bank of America, BBVA, Capital One, CIBC, and JPMorgan Chase have invested in job training and reskilling projects.

Over 21,000 employees have been aided by Bank of America''s career tools and expertise. Consistent training of new technologies and certifications is an investment in shaping the workforce of the future and will help to ensure that employees remain ahead of current trends and industry demands.

Look to data and employee metrics

We always monitor data to further clarify what we should prioritize internally in order to improve our AI reskilling initiatives. A recent LinkedIn study found that today''s measures assessing the effect of training programs relied mostly on soft metrics, such as completion rates, satisfaction scores, and employee feedback.

This is a missed opportunity as business leaders can and should focus on using harder metrics that measure business value, including increases in employee retention, productivity, and revenue, to gain the most useful insights from their reskilling initiatives. If it is not working well, businesses may involve using new technology or tools or modify their program and overall experience to make it successful in the future. By doing so, they will continue to remain ahead in the competitive battle for talent.

Future-proofing starts now

Jamie Dimon''s latest shareholder letter to JPMorgan investors, he says: "Our most important asset is the quality of our staff." He continues, technology always drives change, but now the waves of technological innovation come in faster and faster.

Since company that reskill their employees are more productive, provide positive economic returns and increase employee satisfaction, there is no better time to start than today.

Databricks is a global financial services company based in Junta Nakai, the RVP and the global industry leader.

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