This story was prepared by Workday New Zealand and is being published by the New Zealand Herald as advertorial.
By Jonathan Brabant, Workday New Zealand Director
How a human-first approach to tech investment will pay off.
Organisations are often tempted to view AI solutions as either quick fixes or enhancements that can be layered onto existing legacy systems. This mindset can lead to missed opportunities, suboptimal results, and unhappy employees.
The AI market size is expected to reach a significant US$407 billion by 2027, up from US$89.9 billion revenue in 2022, according to Forbes. In addition, 64% of businesses expect AI to improve productivity. While reports indicate many are worried about job losses, others forecast a future where AI creates jobs and enhances employee experience.
If we take a human-first approach to tech investment, we will see greater benefits. Implementing solutions that focus on amplifying human capabilities ensures investments are practical and aligned with the needs of users, resulting in better integration, scalability, and effectiveness.
Understanding the human-first approach
A human-first approach emphasises the alignment of tech investments with employee needs and organisational goals. Rather than deploying AI solutions as standalone, they are integrated into a broader strategy that considers how technology can enhance workflows. PwC states human-led investment not only solves business problems more effectively but drives higher returns.
Consider a public sector agency looking to implement an AI-based system for managing its money. The AI capabilities need to be built into the application where the finance team spends most of the time, the core accounting system. If the finance data has to be lifted out to a standalone AI system, it creates unnecessary complexity, leading to poor uptake. However, if the human-first approach is applied, the AI is embedded into the core accounting system - For example, the Workday Journal Insights AI feature continually monitors accounting entries as they’re posted to detect and flag anomalies. It also provides a recommended correction whenever possible.
Aligning technology with employees
McKinsey researchers highlight that in the past six years AI adoption has remained at about 50%, while this year adoption has jumped to 72%. Half of respondents say AI has been adopted in two or more business functions, up from less than a third in 2023. Ensuring investments yield maximum returns requires understanding specific challenges and needs of those who will actually use the tech.
Incentivising a human-led approach, PwC’s study highlights that when organisations adopt technologies with a focus on user experience and ease of integration, they see improved adoption rates and greater overall effectiveness.
To bring this into a real-world context, a retail or hospitality company may deploy a new AI-driven inventory management system. If the system is designed with input from store managers and employees, it will more likely include features that address their specific pain points, such as automated restocking alerts or user-friendly dashboards.
A human-first approach also prioritises how seamlessly the technology integrates with existing systems and simplifies adoption. This is particularly important when dealing with AI solutions, which can be perceived as complicated or disruptive. To ease transitions, employees should be involved early on in the development process. Through qualitative research sessions, employees can share their challenges and ideal outcomes.
Changing business models for enhanced value
Leaders know success starts with a strong business model. Statista finds around 90% of businesses believe they will have to make changes to their business model, or have already changed their business model in order to stay economically viable by 2023. In addition, 64% of the respondents believe they need to build new digital businesses.
The principles of a human-first approach can be embedded into every facet of the business strategy, making it easier to rationalise targeted technology investment. The business model can also prioritise talent, fostering skills and innovation required to leverage AI in the workplace. By prioritising ease of use, integration and scalability, organisations can make informed investments that deliver tangible benefits and empower teams.
For the last 10+ years, Workday has intentionally architected its platform to deliver the full value of enterprise-grade AI, building a uniquely robust AI foundation based on data and business context. AI in only as useful as the quality and relevance of the data, and Workday has the largest, cleanest set of finance and HR data in the world - leading to more accurate, relevant and organisation-specific insights. Workday has also deliberately pursued a human centred approach by developing its AI responsibly, by advocating for proactive AI regulation all around the world, that balances both innovation and risk. For Workday, a big part of its mission is deliberately building AI solutions to amplify human potential instead of replacing it.