*The Reality Behind AI’s Hype*
By Chandler C. MorseVice President of Public Policy, Workday
The responsible integration of AI into business processes
Practical steps to enable AI adoption and literacy across all levels of the organization
How policy is helping to drive trust in AI
The conversation about AI goes beyond its revolutionary potential, delving into important ethical considerations, economic implications, and the interaction between humans and machines.
To further explore this topic, I recently talked with Natalie Carruthers, chief associate success officer at Blue Yonder, a supply chain management organization; and Dan Cohen, CIO of The Amenity Collective, a facilities management company, about AI challenges and opportunities. Together, we delved into how to develop trust in AI and thoughtfully integrate it into business processes.
Let’s break down the key insights from our conversation.
A pivotal revelation from our conversation was the unanimous agreement on the crucial role responsible AI integration plays in unlocking the vast potential harbored within AI. In fact, according to the Workday “Global AI Indicator Report,” there’s a correlation between an organization’s AI maturity level and the benefits it sees from the technology. The top 33% of companies that we surveyed are able to work faster and more efficiently with AI, while also finding opportunities to reduce risk.
Both Carruthers and Cohen echoed the sentiment that approaching AI responsibly goes beyond mere efficiency gains. For Blue Yonder, AI is a sustainability engine, enhancing experiences for associates and customers, pushing us beyond simple optimization to holistic improvements.
In an increasingly digital world, Carruthers underscored the importance of weaving AI and machine learning (ML) into Blue Yonder’s operations for enhanced supply chain management and the continuous growth of the team. Similarly, Cohen spotlighted the significant strides The Amenity Collective made in transitioning to proactive processes and harnessing AI for predictive models to enhance retail and hospitality interactions.
Amidst the buzz surrounding AI, it is imperative to distinguish between exaggerated claims and genuine applications. As a company, Workday has been innovating with AI in the HR space for nearly a decade. However, with the emergence of large language models, the hype around AI has reached an unprecedented level—giving the impression that the world has stumbled upon a technology that has, in reality, already been refined over several years.
While some aspects of AI may seem like mere novelties that offer little practical value, there are also concrete use cases for this technology. For instance, the adoption of a skills-based approach to employment offers the possibility of expanding opportunity and leveling the playing field, increasing agility, and expediting recruitment. By interpreting and helping organize large datasets on skills, AI is a game changer when it comes to operationalizing skills data to produce actionable inferences and facilitating informed decision-making, particularly crucial in times of uncertainty or where the job market is volatile, such as during an ongoing pandemic.
The real strength of AI lies in its ability to empower and equip individuals with practical tools and solutions that are measurable and effective. Furthermore, Workday research found that IT leaders will most likely be the ones expected to make a company’s AI deployment a success. This sentiment rings true for Cohen. In sharing The Amenity Collective’s innovative approaches to leveraging technology, Cohen highlighted some of the ways that AI is revolutionizing business operations and enhancing customer experience. For instance, the aquatics division of The Amenity Collective used real-time weather data to predict pool maintenance needs, a strategy that proved useful during the unpredictable COVID-19 pandemic. Additionally, smart supply chain management further ensured service reliability for clients, steering clear of price surges.
Amidst the widespread and growing awareness of AI’s ethical dimensions, it’s pivotal for organizations to embed responsible AI practices into their strategies. This necessitates a proactive approach, ensuring that AI deployment aligns with ethical principles. At Workday, we’ve internally cultivated a robust responsible AI program. This framework, backed by leadership commitment and rigorous review processes, underscores our dedication to upholding AI ethics and fostering transparency.
To address concerns about trust in AI technology, we are not relying solely on our own program. With the goal of building trust, we are actively working with governments around the world to drive the adoption of smart AI safeguards that people can rely upon to know that AI was developed and deployed responsibly. For instance, Workday was an early champion of the NIST AI Risk Management Framework, providing it with its first implementation case study. In addition, we are working with Congress to advocate for a skills-based approach as well as agencies implementing the White House Executive Order on AI and federal guidance on AI acquisition. We are pleased with the overall direction of the EU AI Act, set for adoption early this year, and are proud to be working with state lawmakers in the U.S. toward advancing a reasonable regulatory framework for responsible AI. To carry those regulatory requirements the last mile to actual practices that can be adopted, we’ve partnered with organizations such as The Future of Privacy Forum to advance workplace AI best practices.
When it comes to policymaking in relation to trustworthy AI, the opportunity lies in the heightened interest, but the challenge is in navigating the situation toward actual results. At a minimum, we need to focus on risk-based approaches, recognizing that not all applications of AI merit the same level of scrutiny, such as the difference between AI for recommending TV shows or for reviewing spinal X-rays. The need is for differentiated regulation based on actual influence and consequence on people’s lives.
And even when we have made meaningful progress, we have to be certain we can all work together. There is the need for granular governance and the ongoing process of navigating regulatory frameworks worldwide. The challenge is for AI regulations across the U.S., EU, and UK, and around the world to at least have some level of interoperability, as global compliance is key.
Balancing the speed of technology adoption with considerations of transparency and ethical use is one of our key concerns. We prioritize being transparent with associates about how and why we use certain applications, as well as demonstrating a commitment to our customers’ data privacy. As AI continues to develop and becomes an increasingly integral part of various industries, I believe the question of trust and the importance of maintaining the human factor in decision-making will only become more vital, and we are proud of the constructive role we are playing to develop responsible public policies.
Balancing the speed of technology adoption with considerations of transparency and ethical use is one of our key concerns.
Beyond the policy lens, Cohen also discussed concerns related to data management in AI. I can’t emphasize enough the significance of having a clean, organized dataset, and Cohen has two main approaches to achieving this. First, it involves focusing on creating training sets with a clear objective—using accurate and reliable data that is not only clean, but also free from inherent biases that might influence the models. Ensuring this will result in the use of appropriate data for training the AI system, leading to desirable outcomes.
The second approach is efficient data collection. A consistent process for gathering data across the entire organization, including the tools used and the individuals involved in the collection process, guarantees that the data used in AI provides valuable and accurate results. This also includes collecting relevant, real-time utilization data of assets. The focus is not on collecting all available data, but rather on gathering data directly relevant and useful to our specific purpose. It’s important to manage any inconsistencies or anomalies in the data across different locations.
These approaches highlight the importance of maintaining well-organized datasets, as well as promoting AI literacy beyond just technical teams for a more inclusive and well-informed implementation.
And, as with Workday values, it all comes down to our people. AI proficiency is no longer a specialized skill confined to technical teams—it’s now an enterprise‑wide necessity. Employees must comprehend the broader implications of AI, transcending its technical aspects. This revelation highlighted the symbiotic relationship between technological advancement and human-centric practices as the cornerstone for workforce empowerment.
Carruthers noted the difficulty in finding AI and ML experts due to competition from different sectors; it’s no longer the case that they gravitate toward technology companies. Blue Yonder’s approach to attracting top talent involves providing meaningful experiences that allow employees to make significant contributions to both the organization and the community. The organization prioritizes equipping all employees with a general understanding of AI and its relevance to their roles, including salespeople and recruiters. This knowledge has significant implications for building trust with customers and potential hires.
For organizations embarking on AI adoption, a crucial element for success is fostering widespread adoption and use across all levels of the organization. From executives to IT teams to end users, open communication is key from the outset of AI transformation. And the recipe for failure? That happens when organizations rush to integrate AI without ensuring that the company culture, data, responsible practices, and team are ready.
Amidst this transformative process, staying vigilant is paramount due to the ever-evolving regulatory landscape surrounding AI technology. Success in AI adoption hinges on meticulous planning and preparation. And it’s worth it. AI, with its unparalleled possibilities, not only accelerates human processes, but also introduces innovative perspectives and problem-solving approaches.
