Article: The roadmap to automation readiness - Managing the acceleration mandate in Digital HR

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The roadmap to automation readiness - Managing the acceleration mandate in Digital HR

Balance your automation readiness with the human touch. Do not blindly trust AI.
The roadmap to automation readiness - Managing the acceleration mandate in Digital HR

94% of business leaders believe that AI is critical to business success by 2027, yet 47% say that it creates a fear or concern in the modern workplace, according to a research study on the state of AI. 

The next phase of digital upheaval is here. Modern enterprises understand the potential of technology and its impact on business performance. What should be the right approach to adapt to the rise of artificial intelligence, especially for HR?

The Roadmap of AI adoption

AI adoption is a journey of baby steps. Divya Anand, VP of People Excellence, Amagi Corporation, believes the roadmap to automation readiness starts from placing intelligence before artificial intelligence, i.e. first knowing your people and, thereafter, thinking about process and technology. 

Ganesh Jadhav, HR Director, Physicswallah, shared how the company scaled from ~50 to 11,000+ people in 3 years by understanding the current strengths and future possibilities and then designing timely automation interventions for digital transformation. 

Varun Ramakrishnan, Group Product Manager, Keka, stressed the need for preparedness for automation or HR Tech transformation. He noted that organisations need to get the ‘why”’ right, i.e. understand the ultimate goal and purpose to embark on a ‘journey of optimism’. 

To begin with, organisations and HR should be ready for cultural, financial, and legal implications. It is also important to continually assess that one is going in the right direction, according to Ganesh. 

While it started with a “First Leap” of making processes go paperless through small automation, it evolved to a better HRMS platform and then a scalable ecosystem with business and HR going hand-in-hand. 

Challenges in AI Adoption 

AI adoption often fails because the top management is not aligned or because the organisation is not ready. This is a change management issue. 

Ganesh believes that AI adoption should not be HR-driven but organisation-driven, with adequate cost-benefit awareness. Divya recommends that leaders unveil ‘what are we trying to accelerate’ with due diligence. 

To manage interventions and accelerate ROI from a ‘complete HR tech ecosystem’, organisations must build adequate organisational skill sets. It is important to know what to automate and when to stop. “Let's be careful to not completely do away with the human touchpoint. We must realise the boundaries”, says Divya.  

How to enable AI adoption

A staggered process works best for AI enablement: 

1. Align with the company culture: Divya recommends understanding the people and the organisation, defining a process, and then looking for a technology solution. Not the other way round, i.e. selecting a good-looking UI and trying to force it on your people and process. is essential to success. 

2. Engage the right-skilled people: Have dedicated and high-quality skilled personnel for tech implementation, from requirement gathering to actual coding. Engage with functional experts who understand people, along with a technology person who understands the solution architecture, system architecture, and data architecture. 

3. Go beyond data collection: Any system implementation incurs data collection, but it is important to think about which data really matters. 

4. Implement through iterations: Any automation is an iterative process. Initially, people may not know what to expect in the system, but gradually, they will start suggesting creative ideas. To achieve results, first plan for the first launch and improvise through phases. 

5. Build for integration and scale: Resistance to change is real. Varun shared that organisations want multiple solutions, with each solution going deeper into the subject. However, experts must be able to build holistic outcomes. Integration is critical.

6. Think long-term scale: Pick a one-stop-shop platform scalable for future use. “Currently, many companies are stuck with multiple tools and are not clear on how to come out of it. So, do match your company's requirements with the platform and ensure that you pick the right automation platform for your business”, recommends Varun. 

7. Make leaders role models: Divya shares how leaders need to walk the talk: adopt the system first, showcase it, and become guides and coaches through transformation. 

Technology has its limitations – a logical algorithm cannot define people behaviours with 100% accuracy. So, leaders must constantly question how much it is wise to depend on technology and automation.

 “Artificial intelligence is nothing without human intelligence and human touch” Varun

Human aspects like the cultural readiness of the organisation, the emotional readiness of people, data privacy and trust issues, etc., must be addressed. From an employee's perspective, there are genuine concerns. 

For example, if performance management feedback is being given by a robot, people will be concerned about their job security because it may be biased. If a Learning Management System has only digital content without coaches or mentors, the learner experience will be impersonal. 

While ChatGPT may give creative answers, they are often very repetitive and templatised. Leaders must know where to stop, especially around sensitive, personal and ethical matters. They must creatively brainstorm and imbibe a human touch, which factors in the cultural and social nuances. Only a human can bring in that context. 

“Balance your automation readiness with the human touch. Do not blindly trust AI”, quips Varun.

For this, Ganesh suggests HR build the right skillsets. “HRs need to understand how technology works, such as how APIs get connected or how logic is built into software. This will help them know how tech impacts at the user end and to use AI tools for HR transformation effectively”, says he. 

Above all, HRs should show patience during any tech implementation, allowing technology partners to build right and employees to absorb change. Pallavi outlines this as a journey of bringing synergies between HR and business. 

Divya agrees, “HRs must be an alchemist, a detective, a lawyer and start looking at connections because a lot of subjectivity comes from your human touch points. Build your stories and present your stories. Unlock the Sherlock in you”, says she. Because, ultimately, organisations are dealing with what is most important for us, i.e. people and their emotions, HR leaders have to be curious.

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Topics: Talent Management, HR Technology, #SMEcorner

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