The last mile in Artificial Intelligence (AI) deployment is proving to be a challenge as enterprises struggle to add speed and scale to their go-to-market efforts.
An AI-Automation Center of Excellence (CoE) goes much beyond speed and scale, adopting a business value-led approach to automation.
Amid a cost and talent crunch, strategic partnerships will be key to rapidly developing next-gen automation solutions without significant capital investment.
In a recent survey involving Artificial Intelligence (AI) professionals, 64 percent stated that it took their organizations at least a month to implement a new AI model – while 20 percent observed that the deployment time extended up to six months or more.
The long last mile is a real challenge for AI professionals. How can they add speed and scale to their go-to-market efforts?
Here is where an AI-Automation Center of Excellence (CoE) can make a drastic difference. It accomplishes three critical outcomes. One, it standardizes deployment for faster time-to-market. Two, it establishes leadership in defining the requirements for a successful business case. And three, it achieves optimal use of resources to implement projects with higher efficiencies and at significantly reduced costs.
Let’s see how CoEs accomplish these outcomes.
An effective AI-Automation CoE leverages enterprise-grade platforms and human-automation collaboration to enable the rapid introduction of models into workflows. This not only allows robots in the system to access and apply these models in real-time but also creates a loop for human feedback and continuous model improvement. Additionally, they drive automated extraction, transformation, quality assurance and management of data with centralized governance and compliance.
The AI-Automation CoE goes beyond speed to achieve automation at scale. It seamlessly integrates technology, processes and people to deliver value-led business outcomes beyond operational and cost efficiencies. By taking a business-led approach to automation rather than viewing it as mere technology adoption, it blends business context with Robotic Process Automation (RPA), AI-driven technologies, process mining and advanced analytics – and thus delivers transformational outcomes across the enterprise. Such an approach integrates the rampant process fragmentation that poses a challenge to organizations, as they deploy automation in silos across key areas. The CoE thus moves the needle from task automation and business process automation to intelligent automation.
Forging the right partnerships can help develop next-gen automation solutions leveraging AI, machine learning, optical character recognition, internet of things, data science and analytics, platforms, low-code tools, process intelligence, chatbots, cloud and other innovative technologies. In the face of a cost and talent crunch, strategic and operational third-party partnerships to develop CoEs can rapidly deliver cost-effective automation, speed and scale – sans high investments in the automation infrastructure.
The time is ripe for organizations to scale up business transformation with AI-driven automation CoEs. The benefits are multifold and way too important to ignore – higher speed and precision, automated predictions and decisions, increased productivity at a reduced cost, enhanced accuracy and improved customer experience.
In the next blog, we will look at how we can leverage human-machine convergence to drive AI-led automation at speed and scale.
Read ISG’s recent report on what makes WNS stand out as a ‘Leader’ in Intelligent Business Automation
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