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Beyond Build vs Buy Software for Employee Experience: What’s New In The Era of AI (Artificial Intelligence)

by
Mindy Honcoop
on April 02, 2024

Human Resources (HR) teams have been using forms of AI to automate work. They use business applications like Applicant Tracking Solutions (ATS) and Human Capital Management (HCM) solutions. However, emotions within the HR community vary widely regarding AI, from fear to excitement and experimentation. As headcounts shrink in HR Teams, organizations ask leadership to do more with less.
Some embrace AI’s potential to streamline processes and enhance experiences; others hesitate, overwhelmed by digital transformation’s pace. Welcome to the build vs buy software pivotal decision.

The answer to build vs buy software question goes beyond business use cases and technological adoption. Organizations need to strategize on their “AI readiness” HR is at a critical juncture.
HR must lead discussions, driving initiatives alongside board members, executives, and business leaders, avoiding passivity, and lagging behind.

This article aims to shed light on AI integration complexities. It equips organizations to make informed HR decisions.

The Advantages of Building AI Solutions Internally  

Developing AI solutions within organizations offers the ability to customize to the specific business needs. Tailoring to specific needs and aligning with stakeholder requests can enhance capability and drive desired outcomes. Internal development grants control, facilitates seamless integration with existing systems, and supports ongoing adaptation to evolving organizational needs.

However, internally built solutions necessitate significant time, additional costs for hosting services, and ongoing technical maintenance expertise. Assembling skilled developers, data scientists, and AI experts is expensive, especially given high demand for such talent. Initial project planning, solution architecture, development, adoption, and ongoing support pose significant hurdles for non-tech-savvy organizations.

Structured and centralized data for effective operation also poses a persistent challenge, requiring meticulous attention to data and content management. While staying updated on AI evolution, data privacy, compliance, legal governance, and retaining solution creators is challenging. Without technical expertise, keeping internal solutions up to date with the changing needs of the business becomes difficult, and it often proves cost prohibitive.. 

Tim Whitley, an HR Technology leader, suggests that organizations need to assess both their current and future capabilities. While they may have someone who can build a custom tool now, it is crucial to consider whether they will have the resources to support and maintain it eventually. This is the most common argument against building business solutions internally.  

The Appeal of Buying a Commercial AI Solution with HR Domain Expertise 

Purchasing a pre-built HR AI technology platform offers organizations the ability to launch a solution, specifically designed and developed for HR business challenges, that has been developed with best practices and industry expertise.  

These “out of the box” solutions tackle process and system challenges and architect software with the AI data models and algorithms, specifically to address the “one to many” scenarios, as they focus on solving the pains of their customers. Leveraging the expertise of AI vendors provides a high level of accuracy and reliability in addressing employee needs and business users needs. Commercial AI solutions can create organic and synthetic data sets that are used to train large language models and ensure the accuracy of output. Ongoing support, training, updates, and maintenance provided by the vendor alleviate the burden on internal resources, allowing HR departments to focus on strategic initiatives and employee development. Partnering with a vendor ensures staying updated on AI tech changes and legislative actions.

HR teams can build partnerships with their solution provider’s Customer Success Managers, to help educate and guide them in better understanding how the AI works so they can be the “human in the loop” in the ongoing training of the AI models, specific to the HR domain and to them, as a customer. These Customer Success Managers also advise HR/IT teams, aiding in digital workplace strategy and change management processes.

Utilizing a vendor/partner provides the opportunity for companies to proactively get ahead of internal digital roadmap planning. Leveraging an external vendor solution frees up their time for other internal projects, that helps them continue down a path towards additional automation and improved productivity. They can also utilize the time created to improve data accuracy, data, and content consolidation, and increase AI skills and talent capabilities within their team.  

Organizations may need to adapt their processes to fit the capabilities of the commercial AI platform. This may require an upwards adaptation which improves current processes. This will be a shift away from manual processes to embrace automation. Integration into current communication and HR systems may also be a challenge.

Key Considerations for Build vs Buy Software Decision-Making  

When weighing the decision of building and buying an HR AI platform, organizations should consider several crucial factors. Assessing technical capabilities, customization needs, time and cost implications, integration capabilities, and compliance with data privacy. Evaluating the current state of data cleanliness and centralized knowledge management is foundational for successful implementation.  

“It is not really a ‘build vs. buy’ decision…it is really a buy vs. create, build, maintain, document and staff a solution.”

John Carney, an Enterprise Solution Architect and Technologist

Navigating Risk and Governance of Build vs Buy Software

When it comes to AI, risk and governance are critical considerations. Generative AI presents challenges such as inaccurate results, legal risks, privacy concerns, a lack of transparency, and systemic bias. Global laws regarding employment practices, policies, and AI are ever changing. Companies need human verification of outputs to ensure AI technology is correctly being trained and continuously learning and adapting to these evolving inputs. The ability to audit responses to questions asked is also important should documentation be needed for future legal counsel.  

In the realm of AI in HR, there is no one-size-fits-all solution. The choice between building and buying an HR AI platform depends on an organization’s specific needs, resources, and technical capabilities. As John Carney summarizes, the conversation around AI in HR is not simply a build or buy decision.  

Companies constantly underestimate the time it takes to develop solutions outside their core competencies. There is time to project manage, document, train, and update internally built solutions. When it comes down to actual benefits of a custom solution, the costs outweigh the results,” states Mr Carney.  

It is do you have the internal resources, technical expertise, legal and compliance knowledge, and budget to support the everchanging costs of AI consumption services? Organizations must weigh the costs and benefits of each approach to determine the best path forward

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ABOUT AUTHOR

Mindy Honcoop

Mindy Honcoop is an experienced People Leader now serving as MeBeBot’s VP of Customer Strategy and Operations. Previous HR advisor to Care.com, Spiceworks Ziff Davis, HomeAway.com, Blackbaud, and Expedia.