By Raghu Ravinutala
As the world embraces the post-pandemic environment, enterprises are undergoing rapid business transformation. Companies are reshaping their marketing, HR, sales and customer support strategies to survive and then thrive in the new normal. Now more than ever, technology driven innovation has become important for devising and executing novel ways to bridge the gap of demand and supply in these unprecedented times.
The biggest problems enterprises are trying to solve include – engaging with customers and employees more digitally without losing personal touch, increasing automation and safeguarding business from disruption, marketing and selling digitally, and onboarding and training employees remotely. Before covid, artificial intelligence and deep technology innovation was being rolled out over several years with pilots and proof of concepts. The pace has completely changed now. Enterprises are looking to swiftly deploy AI solutions across business processes. Hence, there is a critical need to democratize AI to enable significant outcomes for enterprises and consumers across the spectrum.
Technology is now on the cusp of moving beyond augmentation that replaces a human capability to augmentation that creates superhuman capabilities. This is what leaders need to harness and drive. Gartner predicts that by 2022, 70% of customer interactions will involve emerging technologies such as machine learning (ML) applications, chatbots and mobile messaging.
However, the path to AI can be un-conventional and even daunting at first because a lot goes into building a perfect solution that meets specific business needs. The key lies in thoroughly assessing which Conversational AI platform is best for an organisation. A meticulous Conversational AI platform is always accompanied by an in-depth guide for C-suite executives and decision-makers, to utilize the capabilities of AI for optimizing and streamlining business processes across industries.
It has a developer API and software development kit (SDK) so that third parties or clients can extend the platform with their customizations. Having omni-channel deployment facility is another good marker, where smart bots and virtual assistants are seamlessly integrated across platforms like social media, website, Google Business Messages, WhatsApp for Business and Alexa.
This brings us to the second part of the ongoing conversation around AI/ML. It’s well and good to illustrate the benefits of AI/ML, but how quickly will these automation technologies actually see the light of day? When it happens, will it replace human jobs? Factors that determine the pace and extent of automation include the ongoing development of technological capabilities, the cost of technology, competition with labor including skills and supply and demand dynamics, cost savings, and social and regulatory acceptance.
The key tenets of democratizing Artificial intelligence are
- Simple front-end and powerful backend: One of the key reasons chatbots and voice assistants have evolved into the most widely deployed use-cases of artificial intelligence is the simple , natural interfaces that can be used by anyone. Organizations should look at how powerful AI applications are delivered to users over simple and intuitive interfaces like chat and voice and on platforms that are most widely used such as WhatsApp, Slack, Microsoft Teams etc.
- Data-efficient algorithms: The impediment for AI deployment many times is lack of large data sets for the application in consideration. There have been algorithms and techniques to use global and generic datasets which require minimal custom application specific datasets to start with and applications are designed in a way to keep adding to the dataset through the usage of the application. The outcomes of this are faster deployment cycles and continuously improving applications.
- Low-code / No-code platforms: The ability of an organisation to deploy AI applications is sometimes limited by the number of trained developers in the organizations. Enterprises are seeing that the use of no-code and low-code applications enables business users and non-developers to build and deploy AI applications enabling larger coverage and ROI driven applications.
Tech innovators and industry leaders need to actively spearhead efforts that advocate the democratization of Artificial Intelligence, by improving access and encouraging adoption. For enterprises, it means making intelligence accessible for every organization, and every employee. Technology vendors releasing AI and ML products can make a start by determining which part of the value chain their tool or platform will be democratizing. Data is the heart of artificial intelligence, but AI does not belong to just data scientists any more. These tools empower the workforce and put capabilities in the hands of non-tech experts.
It frees up experts to work on the most cutting-edge applications of the technology rather than getting bogged down on mundane but commercially important projects. Within the current pandemic context, Gartner cites that AI/ML optimization and natural language processing (NLP) are providing vital insights and predictions about the spread of the virus, and the effectiveness and impact of countermeasures.
Undoubtedly, there is always resistance to change, but leaders can inspire people to embrace new technologies by fostering understanding of benefits for business. It is essential to invest in training to integrate AI with legacy business intelligence (BI) tools. Lowering barrier to adoption is critical in technology acceleration. It fundamentally reshapes the behavior of users and makes data and applications part of their lives.
The future of AI involves the optimum use of hardware and software to ‘swiftly’ analyse big data, track patterns and derive insights to build actionable, outcome oriented business strategies with this intelligence. As a tech enabler, we are seeing firsthand the massive advantages for well-capitalized companies when they integrate artificial intelligence solutions into business functions like customer experience and support.
Business leaders are experiencing significant cost-savings, 10x leads and impressive leaps in revenue and customer satisfaction scores. Getting business users to participate is challenging but ultimately rewarding. It injects more peoples’ perspectives into the creative process, while at the same time, democratizing AI.
The author is CEO & Co-founder, Yellow Messenger