Artificial Intelligence

The Most Strategic Agenda in CXOs discussions: AI

Leadership teams are increasingly seeing AI as a key component of their strategic agenda for their organizations.
The Most Strategic Agenda in CXOs discussions: AI
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Chief Strategy Officer, Fractal Analytics
4 min read
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With Artificial Intelligence delivering demonstrable and measurable business impact across enterprise functions – Sales and Marketing, Customer Service, HR, Finance – CXOs are no longer seeing AI as simply part of the technology function. AI transformation requires multi-stakeholder collaboration, access to multiple data sources and strong technical and business process skills. Given that, and its potential to impact existing business processes and invent entirely new revenue models, AI is increasingly getting a seat at the CXO table.

Leadership teams are increasingly seeing AI as a key component of their strategic agenda for their organizations. But piecemeal AI deployments will not deliver the full impact of AI. To harness AI’s potential for business, it needs to be interwoven into the fabric of an organization and its culture. In this article, we will discuss 4 strategies that CXOs need to adopt, that will help power an AI transformation for their business.

Assessing Enterprise Readiness for AI

    The first important question organizations need to ask themselves while developing their roadmap for AI transformation is – how well-equipped is our organization to build and deploy AI-led solutions? Should we build, buy or invest? Internal skill assessment is needed to understand if their current workforce can handle their AI initiatives. While a few organizations may have some level of AI capability in-house, they may lack of specialized skills needed to perform niche projects. Assuming these skills are not available in-house, enterprises need to consider collaborating with external vendors. Companies also need to explore whether an external organization can provide potentially industry- or vertical-disrupting solutions. In such cases, it might be wise to assess an investment opportunity with these organizations and reap the benefits of the innovation that they would provide.

    Moving from a Function Mindset to a Process Mindset

      Traditionally, technology procurement has been at a department / function level i.e. finance teams buy accounting software, HR teams buy talent management software, sales team purchase CRM etc. Organizations would actively need to move beyond a function-centric mindset to a process-centric mindset. AI cases typically span multiple functions and tap into multiple data sources to provide seamless value across teams. This requires process-centric view, with a consensus across multiple stakeholders for delivering successful AI implementations. Additionally, procurement of AI applications would likely come from the budgets of multiple beneficiaries across functions..

      Overcome Resistance to Change by Being ‘Innovation-First’

        Implementing AI requires consensus and engagement of multiple stakeholders, and it is not that hard to anticipate that there will be some resistance to change. It is critical to reorient the mindset of these stakeholders to be ‘innovation-first’. To overcome this and receive their buy-in, enterprises need to educate people on the clear, topline and bottomline benefits of an AI transformation. To further reduce defensiveness in implementing AI-led processes, it is also worth exploring setting innovation objectives for stakeholders as part of their performance metrics.

        Re-Skilling and Re-deployment of the Workforce

          AI often raises understandable questions around loss of jobs and the new skills required for performing new tasks. Therefore, it becomes critical to re-skill and re-deploy the workforce to enable an AI transformation. This requires organizations to map the existing skills of their workforce and identify what new direction they could be reskilled and redeployed in. Concerted efforts will be needed on the part of multiple teams – operations, HR, finance – to map skills, conduct learning programs and ensure that upskilling and deployment is complete.

          An AI transformation for enterprise is essentially a large-scale business re-engineering and re-orientation exercise. And as these transformations go, it is important that they have the attention of the C-Level to implement enterprise-wide strategies to ensure their success.

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