AI in the workplace: 10 key use cases, benefits, and challenges
September 12, 2023
The implementation of AI in the workplace helps augment staff performance, streamline human resources operations, improve employee experience, and promote cross-team collaboration.
Find out how AI services and software solutions can support your workforce and help your organization achieve its corporate goals.
AI trends in the workplace
57%
of executives would invest in AI and automation in the event of an economic downturn
Mercer’s Global Talent Trends Study, 2023
77%
of workers believe their organizations will provide training on AI-driven job changes
Mercer’s Global Talent Trends Study, 2023
79%
of respondents achieved full-scale deployment for 3+ types of AI applications
Deloitte’s State of AI in the Enterprise Report, 2022
76%
of respondents plan to increase their investments in AI to gain more benefits
Deloitte’s State of AI in the Enterprise Report, 2022
50%
of employees will need reskilling initiatives by 2025 to embrace AI-enabled work trends
WEF’s Future of Jobs Report, 2020
Acquiring AI talent
Acquiring AI solutions
Scheme title: AI talent and software acquisition options
Data source: deloitte.com — Deloitte’s State of AI in the Enterprise, 2022
10 applications of AI in the workplace
From recruiting and onboarding to business process automation, companies are increasingly propelling the adoption of AI in the workplace and its influence on our careers and the labor market.
Headhunting
The effects of AI begin even before we set foot in a new office. For example, predictive analytics software powered by machine learning algorithms can segment and filter suitable candidates based on resumes and relevant metrics, matching their job experience with the required profiles. For instance, the recommendation systems of major job search social media leverage ML, including LinkedIn’s engine and its Recruiter feature for candidate ranking.
Scheme title: LinkedIn’s recommendation system architecture
Data source: The AI Behind LinkedIn Recruiter search and recommendation systems
Our team will augment your workflows with AI
Benefits of AI in the workplace
Adopting artificial intelligence and related technologies in a business scenario can benefit both your staff and the organization as a whole, resulting in enhanced performance, cost optimization, new job opportunities, and a better work experience.
Increased productivity
Deloitte’s 2023 Global Human Capital Trends Report highlights that artificial intelligence and machine learning will contribute to a 37% increase in labor productivity by 2025. In fact, data-driven decision-making will enhance human impact at work and organizational performance.
Cost reduction
According to Bain & Company’s 2023 The Augmented Workforce Report, intelligent automation will lead to a greater focus on higher-value work (including problem-solving, creativity, and interpersonal communication) and a 21-30% cost reduction.
New job positions
The World Economic Forum estimated that by 2025, AI-powered automation could create 97 million new jobs (data analysts and scientists, business development professionals, digital transformation specialists, etc.), compared to the 85 million lost (such as accountants or data entry clerks).
Employee satisfaction
In its 2022 State of AI in the Enterprise Report, Deloitte pointed out that 82% of respondents expect AI to enhance job satisfaction. Specifically, many AI adopters see value in leveraging automation to reallocate workers from repetitive tasks to creative activities.
Bias-free decisions
Adopting AI-powered analytics helps minimize human bias and its impact on workplaces and careers. From automated candidate screening to accurate, data-driven staff performance assessments, professionals can expect a fairer approach to recruitment and talent management.
Accuracy and compliance
While AI's reliance on data (including sensitive information) can raise concerns among regulators and should be addressed carefully, its adoption can be beneficial for corporate compliance. For example, AI-based RPA can increase reporting consistency and accuracy by about 80%, according to Deloitte, while lowering the number of employees who have access to sensitive information.
Risk mitigation
AI safeguards your workforce from operational risk in industrial scenarios via anomaly detection and predictive maintenance, minimizing the likelihood of failures and consequent disasters. It can also identify signs of fatigue or psychological discomfort to trigger targeted support initiatives.
Inclusive workplaces
AI fosters workplace diversity and inclusivity by enabling data-driven skill assessments and blind hiring. For instance, AI-based talent intelligence platforms can rank candidates based on their actual expertise while masking identifiable attributes and protected traits (age, gender, disabilities, etc.).
AI implementation roadmap in the workplace
Organizations implementing AI in their workplaces usually go through these key steps, which can vary based on their business scenarios, selected use cases, and technologies involved.
1
Business needs analysis
Assess business needs and expectations via discovery workshops, interviews, and process observations
Audit the existing technical environment
Highlight the project's scope, objectives, deliverables, and timeframes
Define the future solution’s functional and non-functional requirements
2
Initial data analysis
Carry out an exploratory analysis to map and assess available corporate data sources
Identify external data sources, such as public databases
3
Solution design
Design the AI solution’s architecture, main modules, and features
Define a project plan, budget, and timeline
Identify a suitable tech stack based on the technical and business evaluation
Optionally deliver a PoC to ascertain the AI solution’s feasibility, financial viability, and potential limitations
4
Building the AI solution
Carry out data pre-processing, including data cleansing, annotation, and transformation
Outline the solution’s assessment criteria
Train one or more AI models via supervised, unsupervised and reinforcement learning to achieve the desired output
5
Integration and rollout
Integrate the AI model into the solution to power its features with the model’s output
Deploy the product to the target environment (on-premise or in the cloud)
6
Support
Retrain the AI model with new data over time to enhance the accuracy of its output
Perform ongoing maintenance, fixes based on user feedback, and upgrades with new features
Challenges and guidelines for adopting AI in the workplace
Despite the payoffs unlocked by the use of AI in the workplace, adopting and scaling it across your organization can involve a range of business and technical challenges. Here are a few tips to mitigate such issues while maximizing the value of AI for your workforce.
Barriers
Insufficiencies
Difficulties
Ethical risks
Scheme title: Barriers and risks when adopting AI in corporate scenarios
Data source: deloitte.com — Deloitte’s State of AI in the Enterprise, 2022 deloitte.com — AI for work relationships may be a great untapped opportunity, 2022
Use case identification
Issue
Implementing AI solutions can be very impactful but also time-consuming and financially demanding due to their complex architectures, processing power requirements, and long algorithm training times. Deciding whether AI represents a better option for your use case over conventional technologies is essential for making its adoption worth the effort and investment, maximizing ROI and ensuring stakeholders’ and executives’ buy-in.
Recommendations
It makes sense to implement AI when facing serious inefficiencies affecting key business processes, which cannot be solved with "traditional" software solutions. Investing in AI can also be a good choice when it comes to improving the most profitable corporate functions depending on your industry. For example, McKinsey mentions supply chain management for retailers, product development for high-tech corporations, service operations in telecommunications industries, product assembly in the automotive sector, and risk management for financial services.
AI and the future of work
In recent years, together with other technological advances, AI has reshaped our physical and digital workplaces. However, its adoption may raise concerns due to potential skill gaps, along with the tension between regulations and AI’s need for big data. To address these and other implementation challenges, rely on Itransition's expertise in AI consulting and development.
