AI retraining: a solution to the workers crisis

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by 2025, the World Economic Forum estimates that 97 million new jobs could be created if artificial intelligence (AI) changes the nature of work and affects the new division of labor between people, machines and algorithms. Specifically in banking, a recent McKinsey Survey found that AI technologies can deliver up to $1 trillion in additional value each year. AI continues its steady rise and is beginning to have a profound impact on financial services, but its potential is far from being fully realized.

The transformative power of AI is already impacting a range of functions in the financial services industry, including risk management, personalization, fraud detection and ESG analytics. The problem is that progress in AI is being held back by a global shortage of workers with the skills and experience in areas such as deep learning, natural language processing and robotic process automation. With AI technology opening up new opportunities, financial services firms are eager to gain the skills they need to leverage AI tools and advance their careers.

Today, 87% of workers consider retraining and upskilling options in the workplace very important, and at the same time, more companies are being ranked training of their staff as a top-5 business priority now than pre-pandemic. Companies that don’t focus on driving AI training will fall behind in a tight recruiting market. Below are some important tips for business leaders who want to prioritize retraining efforts in their organization.

Build data literacy with customizable learning paths

Any digital transformation requires leaders to focus their investments on two modern sources of competitive advantage: data and people† First, driving data literacy across the organization helps industry and domain experts (sales, HR, marketing, financial analysts, etc.) collaborate with AI and machine learning experts, which is critical to moving forward than proof-of-concepts and experiments.

To deploy AI tools on a large scale, those employees whose jobs involve interacting with AI systems need to understand how those systems work and what the limitations and limitations might be. Upskilling these individuals may include how to interpret the results of the AI/ML models or how to intervene with AI/ML experts when the results are not correct.

A recent McKinsey research found that effective retraining is 20% more cost-effective than a “hiring and firing” approach, and using the right tools and technology can help companies achieve their retraining goals.

Importantly, before embarking on AI retraining efforts, banks and financial services firms need to understand what results they are aiming for and what skills are required. An employee self-assessment survey that focuses on the skills needed can help companies determine a customized curriculum and plan based on existing skills gaps.

The understanding of a one-size-fits-all training program or whether employees have to spend a lot of time away from the office to take courses is no longer relevant. Using digital learning platforms such as SkillsofUdacityor Udemy, or integrating content into mainstream work systems can make employee retraining experiences more user-friendly. Platforms like walk with me can help employees quickly learn complex software systems, and axonify can deliver 5- to 10-minute microlearning sessions to employees within their daily workflow. For an even more customized approach, companies can choose to build their own programs with the help of industry consultants and professors who are experts in their fields.

Leverage existing in-house AI retraining tools and groups

A Deloitte Research found that 94% of employees would stay with a company if it helped them develop and learn new skills, but only 15% have access to learning opportunities directly related to their job. AI retraining presents a huge opportunity for both financial services firms and their employees, but it can be daunting to consider the money and time investments required for retraining efforts. The good news is that companies can often use existing business tools instead of buying all new software.

Here are three excellent resources to accelerate AI/ML training and deployment:

  • Industry consortia: You may also want to consider joining industry consortia that support your team’s progress and drive employee growth through collaborative groups. For example, FINOS (fintech open source consortium under Linux Foundation) helps to facilitate the processing and exchange of financial data across the banking ecosystem.
  • Cloud service provider (CSP) training and certification programs: Many of the CSPs, such as: AWSGoogle Cloud and Microsoft, offer ML training and certification programs for free or subsidized prices. These self-guided programs range 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 build or change careers.
  • Technology Enablers’ AI-powered solution accelerators: In addition, many companies like: IBMAWSPwC and Databricks provide easily deployable tools and solution accelerators for common data analytics and machine learning use cases that organizations can leverage. Rather than endure weeks of development time, technical professionals such as data scientists, solution architects, and developers (from novice to expert) can use these accelerators to enable faster modernization and upskill talent. At Databricks, our accelerators for financial services solutions help businesses capitalize on the open banking paradigm, by providing free code and training that aid in 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 cultural benefits of providing AI retraining opportunities

Investing in the skills and knowledge of employees can build a positive corporate culture and reduce turnover by increasing employee confidence and productivity, and it creates a more well rounded workforce that increases the effectiveness of teams.

AI reskilling efforts could also help financial services firms make better progress with their diversity, equality and inclusion methods by making learning more accessible to those who have encountered barriers to higher education. To address this and the skills gap, banks including: bank of AmericaBBVACapital OneCIBC and JPMorgan Chase have invested in vocational training and retraining efforts for their employees.

Bank of America’s career tools and resources have more than 21,000 employees find a new position at the company. Consistent training on new technologies and certifications are an investment in shaping the workforce of the future and helping to keep employees ahead of current trends and industry demands.

Look at data and employee statistics

As a leader at an organization focused on data and AI, we always look to the data to show what to prioritize internally – and this includes what to focus on in our AI retraining efforts. In measuring the success of retraining programs and initiatives, a recent LinkedIn research found that current metrics for assessing the impact of training programs relied primarily on soft metrics, including completion rates, satisfaction scores, and employee feedback.

This is a missed opportunity, as business leaders can – and should – consider using tougher metrics that measure business value, including increases in employee retention, productivity or revenue, to gain the most useful insights from their reskilling initiatives. If it doesn’t work well, companies may consider adopting new technologies or tools, or adapting their program and overall experience to make it successful in the future, thus staying ahead of the competitive battle for talent.

Future proofing starts now

In Jamie Dimon’s latest shareholder letter to JPMorgan investors, he points out: “Our most important asset – far more important than capital – is the quality of our people.” He continues, “technology always brings change, but now the waves of technological innovation are coming in faster and faster.”

Since companies that refresher training their employees are more productive, deliver positive economic returns and see greater employee satisfaction, there is no better time to start than now.

Junta Nakai, RVP and global leader in financial services at Databricks

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