Key to Overcome Challenges Faced in Operationalizing AI

In the digital age, top executives consider AI as vital to their businesses and therefore plan on increasing investment in AI. For today’s organizations, AI provides demonstratable value resulting in bottom-line and top-line improvements. The repeatability and scalability of AI provide better process optimization which helps in saving costs and generating higher revenue.

The reality of AI is quite different though. According to Gartner, only 53% of AI Proof of Concepts (PoCs) are ever scaled to production. This shows the large disconnect between building an AI model and the deployment of AI in production. Most data scientists have the skills to design an AI model, but if the IT teams are unable to understand the complexities in the implementation of AI, then the project fails to make it to production. This has been termed the Last-Mile Challenge.

To overcome this last-mile hurdle to fully operationalize a solution, organizations’ success lies in strategic management of the AI journey. In large enterprises, in order to accelerate AI initiatives, effective ModelOps capability helps to eliminate excess cost, friction while protecting the enterprise from unbounded risks.

Many times, Model deployment cycle is very long, so it is critical to determine the length of the cycle depending on the organization followed by establishing parameters to measure improvement. Some of these activities can be automated with the help of a ModelOps solution. Some of the significant challenges in Operationalizing AI are Lack of Integration with existing systems, lack of superior Data Quality, Legacy infrastructure, insignificant Compute Power, and Lack of Interpretability.

The space of Analytics and Data is changing rapidly, which requires organizations to take a step towards operationalizing AI. To remain significant, organizations need to overcome the above-mentioned challenges to achieve autonomous AI. Learn more about moving past the last mile challenge of AI operationalization in the upcoming Virtual Fireside Chat from the industry experts of 451 Research and Innominds. Panelists include Nick Patience - Founder & Research VP, 451 Research, Ravi Meduri – EVP, Innominds, and the virtual session is moderated by Sairam Vedam - CMO, Innominds.  

Register Here: - https://www.innominds.com/achieve-autonomous-ai-for-the-enterprise?utm_campaign=Fireside%20Chat%205%20-Achieve%20Autonomous%20AI%20for%20the%20Enterprise&utm_source=linkedin&utm_medium=social&utm_term=Amitav%20Sahoo&utm_content=FS5

2055 Junction Avenue, Suite 122,
San Jose, CA 95131.

Innominds is an AI-first, platform-led digital transformation and full cycle product engineering services company headquartered in San Jose, CA. Innominds powers the Digital Next initiatives of global enterprises, software product companies, OEMs and ODMs with integrated expertise in devices & embedded engineering, software apps & product engineering, analytics & data engineering, quality engineering, and cloud & devops, security. It works with ISVs to build next-generation products, SaaSify, transform total experience, and add cognitive analytics to applications.

This release was published on openPR.