AI | April 12, 2024
Image: freepikAI is not just a tool for augmenting human tasks but an emerging workforce that merges labor and software into a single market
NFX recently published an article titled “The AI Workforce is Here: The Rise of a New Labor Market” that discusses the merging of labour and software due to the advancements in artificial intelligence. The shift is creating significant opportunities for innovation and new business models, transforming industries by substituting traditional SaaS functionalities with comprehensive AI-driven solutions.
- Traditionally, software has been a tool to help humans work more efficiently. However, AI is changing that by taking on entire jobs by itself, essentially merging the realms of software and labor into one. This means companies might start seeing software not just as a tool, but as an active part of the workforce. As AI starts doing more of the work traditionally done by humans, there’s a huge opportunity for new businesses to emerge. These businesses can use AI to do things cheaper, faster, and possibly better than humans. The convergence of labor and software markets is expected to not only broaden the market scope but also to enhance profit margins.
See: Klarna’s AI Handles 700 Jobs, Targets $20B IPO
- AI can efficiently monitor transactions for compliance and unusual activities that might indicate fraud or violations of regulatory requirements. The ability of AI to analyze large volumes of data quickly reduces the need for extensive teams of compliance officers.
- AI algorithms can assess risk and determine creditworthiness more quickly and accurately than traditional methods. This automation could reduce the need for human underwriters, especially in straightforward, less complex cases.
Likely to Be Transformed
- While AI can handle many analytical tasks, human insight will remain crucial, especially for complex decision-making. Financial Analysts will need to shift from traditional number-crunching roles to interpreting AI-generated data and making strategic decisions based on this analysis.
- While basic customer interactions may be automated, high-level client management and advisory roles will evolve. Professionals in these positions will need to integrate AI tools into their work to provide enhanced, personalized advice, leveraging AI for data analysis and predictive insights.
- As fintech companies increasingly rely on AI, the importance of cybersecurity grows. Professionals in this field will need to focus more on strategic oversight and less on routine monitoring, as AI handles the latter. They’ll also need to develop skills in managing AI security risks specifically.
See: How GenAI Is Transforming Risk and Compliance in Banking
- Innovation roles in developing new fintech products and services will transform as AI capabilities grow. These professionals will need to understand how to integrate AI into financial services and create innovative offerings that leverage technology to meet changing consumer expectations.
Likely to See Increased Demand
- As AI takes a central role in fintech, demand for AI and machine learning experts will skyrocket. These professionals will be crucial for developing, refining, and maintaining AI systems.
- As AI systems become more pervasive in financial decisions, the need for professionals who specialize in the ethical implications and regulatory compliance of AI systems will increase. These roles involve ensuring that AI systems operate fairly, transparently, and within legal frameworks.
- Professionals skilled in change management and integrating AI into existing systems will be in high demand. They will help organizations transition smoothly to new technologies and ensure employees adapt to new tools and processes.
Today’s Workforce vs. AI Software Workforce
The table below illustrates how the AI software workforce will offer distinct advantages in terms of efficiency and scalability, while also presenting challenges in maintaining the human touch and ensuring ethical use of technology. As AI continues to proliferate widely throughout the economy, the landscape of work will undergo significant transformation, requiring adjustments in workforce management, job design, and regulatory frameworks.
| Aspect | Today’s Workforce | AI Software Workforce |
|---|---|---|
| Nature of Work | Primarily human-centric; involves manual and cognitive tasks. | Primarily automated; AI performs both routine and increasingly complex tasks. |
| Availability | Subject to human constraints (e.g., working hours, breaks, vacations). | Operates 24/7 without interruptions, providing constant productivity. |
| Scalability | Limited by human resource availability and training requirements. | Highly scalable; can be expanded instantly with minimal incremental cost. |
| Skill Development | Requires ongoing training and professional development. | Updates and improvements are deployed digitally, allowing instant enhancement of capabilities. |
| Error Rate | Prone to human error depending on skill level and conditions. | Generally lower error rate, with consistent performance not affected by human factors. |
| Cost | Includes salaries, benefits, office space, etc. | Primarily upfront development and ongoing maintenance costs; significantly lower marginal cost per unit of work. |
| Decision Making | Involves emotional intelligence, ethical considerations, and human judgment. | Based on algorithms and data analysis; may lack nuanced understanding without human oversight. |
| Interaction Style | Personal and capable of empathy and adaptation based on social cues. | Becoming more sophisticated with NLP, but still may lack true empathy and understanding of complex human emotions. |
| Job Creation | Creates a variety of jobs across all sectors. | Shifts job creation towards tech-heavy roles; may reduce jobs in traditional sectors but create new types in AI development and oversight. |
| Regulatory Oversight | Heavily regulated based on labor laws, workplace safety, etc. | Emerging regulations focus on data privacy, ethical AI use, and ensuring fairness in automated decisions. |
Image: Freepik/WangXiNaWorkforce Cost Implications and Examples
- AI typically requires a higher initial investment than hiring a human worker.
- AI tends to be more cost-effective over time, especially if the software can replace multiple human employees or enhance their productivity significantly.
- AI systems offer unparalleled scalability and are available 24/7, which can drastically reduce the need for additional human labor during off-hours or peak times.
See: IMF Issues Warning on AI’s Impact on Global Jobs
- Jobs that involve high volumes of repetitive tasks, like data entry in customer service or standard document drafting, show the greatest cost savings when replaced with AI.
- Roles that require handling complex datasets can also benefit significantly from AI due to the high efficiency and lower error rates.
- Positions that benefit from continuous operation without breaks, such as in sales or customer support, can see substantial cost reductions through AI.
Scenario 1: Customer Service
- Human Workers: Typically include salaries, training costs, benefits, and overhead for physical workspace. Customer service representatives might cost the company $40,000 annually per employee.
- AI Software (Chatbots): Initial development and integration might cost $50,000, with annual maintenance and updates at about $10,000. However, one AI system can handle the workload of multiple representatives 24/7.
- Year 1: Human (1 person) = $40,000; AI = $60,000 (initial + maintenance)
- Year 2 and Beyond: Human (1 person) = $40,000 annually; AI = $10,000 annually
- Savings: Transitioning to AI chatbots could save approximately $110,000 over five years per role replaced. This scenario assumes a single AI system can replace multiple human roles, further increasing savings.
Scenario 2: Data Analysis
- Human Analysts: Salaries for skilled data analysts can be upwards of $70,000 annually, plus costs for ongoing training and software licenses.
- AI Software (Data Analysis Tools): High-end systems can be developed or licensed for around $100,000, with annual maintenance costs of around $20,000. These systems can perform complex analyses much faster than humans and handle larger datasets.
- Year 1: Human (1 analyst) = $70,000; AI = $120,000
See: OSC/EY Report: AI in Fintech Use Cases
- Year 2 and Beyond: Human (1 analyst) = $70,000 annually; AI = $20,000 annually
- Savings: AI tools offer substantial savings, particularly due to their ability to handle large datasets and complex analyses more efficiently than human analysts. The five-year savings potential is around $230,000 per analyst role replaced.
Scenario 3: Sales
- Human Sales Personnel: Including salary, commissions, and expenses, the total can reach $80,000 per person annually.
- AI Software (Automated Sales Systems): Initial setup for a robust automated sales system might cost $150,000, with ongoing costs around $30,000 per year for support, updates, and integration.
- Year 1: Human (1 salesperson) = $80,000; AI = $180,000
- Year 2 and Beyond: Human (1 salesperson) = $80,000 annually; AI = $30,000 annually
- Savings: Automated sales systems provide a significant return on investment through continuous operation and eliminating commission payouts. Over five years, savings could total $220,000 per salesperson replaced.
See: AI’s Ethical Dilemma Grows as Innovation Surges
These scenarios showcase that while AI involves higher upfront costs, the long-term savings and efficiency gains can justify the investment, especially in roles characterized by high volume, repeatability, and the need for speed and accuracy.
In Closing
As companies harness AI to enhance or replace traditional roles, they’re not only optimizing operations but are also poised to significantly cut costs, offering a glimpse into a future where digital workers are as commonplace as their human counterparts. This transformation, while challenging, presents a frontier full of opportunities for those ready to embrace the next wave of technological advancement.
The National Crowdfunding & Fintech Association (NCFA Canada) is a financial innovation ecosystem that provides education, market intelligence, industry stewardship, networking and funding opportunities and services to thousands of community members and works closely with industry, government, partners and affiliates to create a vibrant and innovative fintech and funding industry in Canada. Decentralized and distributed, NCFA is engaged with global stakeholders and helps incubate projects and investment in fintech, alternative finance, crowdfunding, peer-to-peer finance, payments, digital assets and tokens, artificial intelligence, blockchain, cryptocurrency, regtech, and insurtech sectors. Join Canada’s Fintech & Funding Community today FREE! Or become a contributing member and get perks. For more information, please visit: www.ncfacanada.org
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- Source: https://ncfacanada.org/the-rise-and-implications-of-a-new-ai-software-workforce/
