Responsible AI deployment: How to reap benefits of Gen AI without the risks

Generative AI has garnered both appreciation and criticism ever since it was introduced to the world. Technology makers have hailed it as a solution that will increase efficiency and save time. However, some feel GenAI will be responsible for job losses.

In reality, it can help boost productivity by gathering all company data in one knowledge base. This empowers employees to easily source information and make informed business decisions. For example, when using Gen AI in a contact centre, you can automatically gather all the data from multiple conversations and brand literature in one place. Then, when faced with a question, an agent simply needs to enter a prompt to get the right answer.

Gen AI offers undeniable benefits, emerging as an essential tool in today’s time to improve lives with its deployment in sectors ranging from healthcare and banking to IT and education, among others. However, it is everyone's responsibility to use AI in a manner that improves lives without risking jobs or reputations. 

Let’s take a closer look at the use cases of Gen AI.

Improving productivity and internal processes

Generative AI can increasingly improve the internal processes of an organisation. For instance, every business collects extensive data, including past product details, customer buying patterns and their interactions with support services. However, this data is useful only if it's readily accessible. Here, Generative AI emerges as a valuable tool.

Organisations can use it to empower employees to effortlessly acquire information through conversation interfaces, eliminating the requirement of expertise in using different databases. Similarly, in product development, businesses can use GenAI effectively by compiling and summarising customer feedback and requirements. They can develop creatives based on text, identify opportunities by predicting future trends and spot inconsistencies in product roadmaps—all by using Gen AI.

Preventing and detecting fraud

Generative AI is extremely helpful in identifying patterns and detecting anomalies within extensive data sets. It is highly effective for highlighting inconsistencies that could signal fraudulent behaviour.

Platform businesses and social media channels that require customer account creation face challenges in implementing preventive measures against fraud. When offenders are caught, they can easily evade restrictions by creating new accounts with alternate email addresses or phone numbers. Even IP address blocking proves ineffective, as they can bypass it using VPNs.

However, AI offers a solution by swiftly identifying these individuals based on their unique "digital fingerprint," which encompasses various data points such as device, operating system, location, access times, and language and grammar usage.

The AI quickly detects fraud and warns potential victims or freezes the fraudster’s account. 

Also Read

Generative AI could help Indian workers save 51M hours a week by 2026: Pearson

Gen AI for better customer service

Generative AI’s obvious benefit lies in enhancing customer experiences through the deployment of AI chatbots. These chatbots offer swift, round-the-clock assistance, ultimately delivering a more cost-effective service to customers. Moreover, this concept extends beyond conventional web chatbots to include virtual assistants integrated into chat applications, voice channels, and even directly into products. Consider, for instance, business chatbots on WhatsApp, guiding customers through products and offering personalised support and advice throughout their shopping journey.

However, to avoid any fiasco due to chatbots, train the AI with relevant data. Ensure it has been obtained lawfully. If you are training your AI on external data sources, or unvetted information from the web, there are higher chances of responses that are not aligned with the company’s brand values. Another way to prevent any risk includes involving humans in the training process.

Use of Gen AI in HR functions

It is often difficult for large organisations with multiple offices to deliver efficient HR services to their dispersed workforce. Generative AI offers several solutions like customising onboarding materials to each employee's location and role. Businesses can use it to ensure that employees stay informed about new policies and procedures, facilitate access to HR-managed information and collect and summarise data for employee performance evaluations. 

It can also help with the recruitment process, which usually spans approximately 30 days, though for certain roles, it may extend over several months. HR professionals go through several resumes and hold numerous interviews for the perfect match. Generative AI expedites this process by quickly scanning extensive resumes to identify ideal candidates. However, maintaining access to human HR specialists is crucial for addressing specific needs.

Conclusion

The integration of AI holds tremendous promise for enhancing various business processes. From streamlining operations to enhancing customer experiences, AI technologies offer innovative solutions that can drive efficiency and productivity. However, it's crucial to recognise that ethical considerations must underpin the utilisation of generative AI. This involves not only safeguarding sensitive data and ensuring compliance with privacy regulations but also prioritising human oversight and involvement.

(Shradha Thapa is Regional Head - OTT India, Infobip, to help enterprises adopt digital communications channels.)