AI adoption is transforming the financial services industry, with 83 percent of financial services executives claiming that AI is critical to the industry's future. Benefiting firms with everything from credit decisions to chatbots, AI is helping companies in the space save valuable time and money and improve the customer experience.
Though AI is becoming more common across all industries, various barriers exist to further AI adoption among consumers and business leaders alike. There are several AI barriers that are common in every sector. However, the financial services industry is highly regulated, making it challenging to adopt new tools quickly. Without addressing the obstacles to adoption, they can impede the progress of AI integration into the financial services field.
Top barriers to AI adoption in financial services
Given the complexity of AI technology and the uncertainty around how the algorithm produces its recommendations, there is a natural hesitancy among both consumers and business leaders around further AI adoption. Commonly known as the black box problem, the mystery behind AI algorithms work can lead to mistrust in AI.
Business leaders have warranted concerns about further AI adoption, including additional costs to upgrade an established business's architecture to meet the demands of AI and the shortage of trained talent that can maintain the AI algorithms and interpret its insights on an ongoing basis. Additionally, with their firm's reputation on the line, business leaders need to trust AI recommendations as much as they do human decision-making.
Whether it's the worry that AI-backed solutions will make erroneous mistakes or fear that their jobs will be replaced, there are several ways to navigate AI adoption challenges. AI barriers can be mitigated through further education of the technology, increased usage, a clear strategy, and confidence among decision-makers that AI will help profitability, ROI, and more.
Removing barriers to AI adoption
Further AI adoption is inevitable, with 52 percent of companies accelerating AI adoption plans because of the pandemic, as the Harvard Business Review reported. Removing the barriers to AI adoption among business leaders and consumers will be a crucial way for technology teams and decision-makers to integrate AI further with ease and company-wide support.
Nurture talent
With the rapid pace of technological advancement we've seen recently, the workforce hasn't been able to keep up fully. Today, there is a shortage of skilled workers in the AI field trained to perform ongoing maintenance to the system and interpret its insights. A lack of talent in cutting-edge technology can keep the pace for adopting new technology slow and legacy and outdated systems in place for longer than necessary.
The talent shortage experienced today will likely correct itself in the coming years as AI and machine learning become more commonplace across all industries. Although more people are studying and seeking out careers in AI, this doesn't detract from the near-term need for more skilled labor.
Today, business leaders can combat this barrier within their own organizations by identifying current talent that shows interest in AI and retraining them to take on this new role. McKinsey noted that 62 percent of executives expect to replace or retrain more than 25 percent of employees in the coming five years. This process will become more common as many companies seek to accelerate AI adoption shortly.
Embrace Software-as-a-Service (SaaS)
For established businesses, investing in AI may have other implications and costs given its legacy systems that are likely outdated. Adopting an AI system into a firm's operations requires significant infrastructure and storage capacity for the system to work as intended and produce quality results.
Rather than overhauling all physical IT systems, financial services firms can turn to cloud-based platforms for storage to allow further AI integration without substantial costs. Whether rolling over to cloud systems completely or taking on a hybrid cloud situation with some physical systems still in place, established companies can more easily adopt AI solutions without the added cost of completely upgrading all IT infrastructure.
Cloud computing is economical for established businesses, but they are also a safer storage option. Cloud solutions update frequently and can download new features automatically. This helps keep systems up-to-date with the latest technology, ensuring robust security functionalities.
Demonstrate the value of AI to all employees at the firm
AI and machine learning are cutting-edge technologies whose processes and functions are often unclear to those who aren't trained in the field. With uncertainty can come a lack of trust in AI and hesitancy around further AI adoption from both those internal and external to the organization.
Gaining company-wide support is a crucial step in a successful AI adoption process, so correctly portraying the value of AI to all employees is necessary for technology teams and business leaders. For employees, there may be a fear that AI systems will replace their jobs, and business leaders may not trust AI systems as much as human decision-making, not seeing further AI adoption as necessary.
Given these hesitancies, decision-makers and technology teams need to ensure employees that AI will provide extreme value for their organization. AI will make many jobs easier and free up many workers' time for less routine tasks. Educating employees at all levels about the purpose of AI in their organization and how it will impact operations will increase employee buy-in, and further AI adoption will be more successful.
Understand the limitations of AI
Part of the misunderstanding around AI adoption also comes from the lack of knowledge around AI's limitations. Though it is a groundbreaking technology adaptable and can make businesses more efficient, many tasks should still be augmented by human interaction to produce quality results.
There are many examples of bias in AI decision-making that can compromise the integrity of the system's use in a business. AI algorithms are primed to make informed decisions with quality data and routine maintenance, though frequent testing should still be in place. The quality of data input into the systems should not be overlooked, and a lack of access to correct and comprehensive data could make the AI systems less effective.
Understand your firm's AI maturity
Not all companies will use AI in the same way, and business leaders need to assess their firm's goals and recognize areas where processes can be automated and improved and where they cannot. To successfully implement AI into a business's operations and avoid many AI barriers, business leaders need a clear plan for reasonable and achievable uses of AI within their firm.
There are many uses for AI within financial services, including risk management, chatbots, processing insurance claims, or making credit decisions. However, there are still areas where human decision-making is required, or AI and humans can work together to produce optimal results.
AI will not be able to replace all workers, so companies should not adopt AI just for technology's sake. Instead, business leaders should identify critical areas where processes can be improved through AI and machine learning and create a strategy for AI adoption. Businesses will see more successful AI integrations with a clear idea of how AI will be used in their organization and how that may change current processes.
Using No-Code AI to help remove barriers to AI adoption
In successfully tackling the various barriers to AI adoption, financial services firms are better able to take advantage of the increased efficiency and better customer experience through AI integration. Businesses of any size can take advantage of AI through a no-code AI solution, like the one offered by Accern, which removes barriers to AI adoption.
The solution offered by Accern doesn't require companies to hire a designated data analyst or computer programmer, so financial professionals at any level can access insights from AI models without the added complexity. Accern constantly updates its database with the latest trends and recent datasets, making its solution valuable and relevant to professionals in the field. Users will have the edge over competitors with access to insights that can't be found anywhere else. Companies can see how valuable no-code AI can be to their business by contacting Accern for a free demo today.
