AI Retraining: A Solution to the Worker Crisis

The World Economic Forum estimates that 97 million new jobs could be created by 2025 as artificial intelligence (AI) transforms the nature of work and influences the new division of labor between humans, machines and algorithms. In banking specifically, a recent McKinsey survey found that AI technologies could deliver up to $1 trillion in additional value each year. AI continues its steady rise and is beginning to have a far-reaching impact on the financial services industry, but its potential is far from being realised.

The transformative power of AI is already impacting a range of functions in financial services, including risk management, personalization, fraud detection and ESG analysis. The problem is that advances in AI are being held back by a global shortage of workers with the skills and experience in areas like deep learning, natural language processing, and robotic process automation. As AI technology opens up new possibilities, financial service providers are striving to acquire the skills they need to use AI tools and advance their careers.

Today, 87% of employees consider reskilling and upskilling opportunities in the workplace to be very important, while more companies rank upskilling their workforce as a top 5 business priority than before the pandemic. Companies that don’t focus on driving AI training will fall behind in a tight hiring market. Here are some key takeaways for leaders looking to prioritize reskilling 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, strengthening data literacy across the organization helps industry and domain professionals (sales, HR, marketing, financial analysts, etc.) collaborate with AI and machine learning experts, which is critical to moving beyond proof-of-concepts and experimentation.

In order for AI tools to be deployed at scale, those employees whose work involves interactions with AI systems must understand how those systems work and what limitations and limitations might exist. Retraining 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 appear incorrect.

A recent McKinsey study found that effective reskilling is 20% more cost-effective than a “hire and fire” approach, and that using the right tools and technology can help organizations meet their reskilling goals.

Importantly, banks and financial services firms must first understand what outcome they are working towards and what skills are required before embarking on any AI reskilling efforts. An employee self-assessment survey that focuses on the skills required can help organizations define a tailored curriculum and plan based on existing skills gaps.

The idea of ​​a unified training program or that employees have to spend a lot of time away from the office to take courses is no longer relevant. Leveraging digital learning platforms such as Skillsoft, Udacity, or Udemy, or integrating content into popular work systems can make employee retraining experiences more user-friendly. Platforms like WalkMe can help employees quickly learn complex software systems, and Axonify can offer employees 5- to 10-minute microlearning sessions within their daily workflow. For an even more customized approach, companies can choose to create their own programs with the help of industry consultants and professors who are experts in their fields.

Turn to internal, existing tools and groups for AI retraining

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

Here are three excellent resources to speed up AI/ML training and implementation:

• Industry consortia: You may also consider joining industry consortiums that support your team’s progress and encourage employee growth through collaborative groups. For example, FINOS (Fintech Open Source Consortium under Linux Foundation) helps to facilitate the processing and sharing of financial data across the banking ecosystem.
• Cloud Service Provider (CSP) Training and Certification Programs: Many of the CSPs, such as AWS, Google Cloud, and Microsoft, offer free or subsidized ML training and certification programs. Varying in topics and tracks from understanding conversational AI to machine learning for business and technical decision makers, these self-paced programs are designed for those looking to learn new skills or to build or change careers.
• AI-Powered Solution Accelerators from Technology Enablers: Additionally, many companies such as IBM, AWS, PwC, and Databricks offer easy-to-deploy tools and solution accelerators for common data analytics and machine learning use cases that businesses can leverage. Rather than endure weeks of development time, technical practitioners such as data scientists, solution architects, and developers (from novice to expert) can leverage these accelerators to enable faster modernization and help upskill talent. At Databricks, our financial services solution accelerators help companies embrace the open banking paradigm by providing free code and training to help 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 cultural benefits of offering AI retraining opportunities

Investing in employee skills and knowledge can build a positive organizational culture and reduce turnover by increasing employee confidence and productivity, and create a more balanced workforce that increases team effectiveness.

AI reskilling efforts can also help financial services organizations make better progress in their diversity, equity and inclusion practices by making learning more accessible to those who have faced barriers in higher education. To close this and the skills gap, banks such as Bank of America, BBVA, Capital One, CIBC and JPMorgan Chase have invested in professional training and reskilling for their employees.

Bank of America’s career tools and resources have helped more than 21,000 employees find new positions within the company. Consistent training in new technologies and certifications are an investment in shaping the workforce of the future and help ensure that employees are always one step ahead of current trends and industry requirements.

View data and employee metrics

As leaders in an organization focused on data and AI, we always look to the data to show what we should be prioritizing internally — and that includes what we should be focusing on in our AI reskilling efforts. When measuring the success of reskilling programs and initiatives, a recent study by LinkedIn found that today’s efforts to assess the impact of training programs rely 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 more rigorous metrics that measure business value, including increases in employee retention, productivity, or revenue, to glean the most helpful insights from their reskilling initiatives. If it’s not working well, companies can consider adopting new technologies or tools, or adapting their program and overall experience to make it successful in the future, and that way continue to stay at the forefront in the competition for talent.

Future security starts now

In Jamie Dimon’s recent shareholder letter to JPMorgan investors, he points out, “Our greatest asset – far more important than capital – is the quality of our people.” He continues, “Technology always drives change, but now the ripples of technology are coming Innovation ever faster.”

As companies that reskill their employees are more productive, generate positive economic returns and experience higher employee satisfaction, there is no better time to start than now.

Junta Nakai, RVP and Global Financial Services Industry Leader at Databricks.