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Home » Trusted, Conversational AI will Drive Productivity & Decision-making – Here’s How 

Trusted, Conversational AI will Drive Productivity & Decision-making – Here’s How 

Techeconomy by Techeconomy
October 3, 2023
in DisruptiveTECH
Reading Time: 3 mins read
2
AI will Drive Productivity & Decision-making

Zuko Mdwaba, Salesforce

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Writer: ZUKO MDWABA, Salesforce Area VP / Africa Executive 

Businesses are embracing AI and increasing productivity across every industry, with 45% of executive leaders reporting increased investments in AI.

Early enterprise adopters are already seeing the benefits, and freeing up more than 30% of time from every employee so they can be more strategic and creative.

Moving forward, every company will undergo an AI transformation to increase productivity and drive efficiency.

As the technology continues to advance, it is becoming easier than ever to apply its insights and tailored content to everyday business decisions.

By infusing trusted AI across every job, business, and industry, together we can unlock a more productive, innovative business economy.

Nowhere is the potential for transformation more clear than with conversational AI – assisting users within their flow of work, enabling them to ask questions in natural language, and receive relevant and trustworthy answers that are grounded in secure company data.

The capability to offer options for additional actions beyond the user’s query – such as a recommended action plan after a sales call, or creating a new service knowledge article – is fundamentally reshaping how people build and interact with business applications to achieve higher performance and job satisfaction.

At Dreamforce recently, Salesforce introduced the next generation of Einstein, its AI technology, bringing conversational AI to any workflow, user, department and industry. This includes Einstein Copilot – a trusted out-of-the-box conversational AI assistant, built into the user experience of every Salesforce application.

The great advantage of this technology is that it can be customised and built to the unique specifications of any business, allowing employees to easily integrate it into their day-to-day work.

For marketers, for example, it means benefiting from automatically generated email copy for campaigns, creating smarter campaign segmentation, and creating website landing pages based on personalised consumer browsing and buying preferences.

In commerce, it means taking care of complex and time-consuming tasks like managing multi-product catalogue data, creating product descriptions in multiple languages, personalising product promotions, and generating search engine optimisation (SEO) metadata that drive conversions.

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Embedding AI assistants into websites will enhance customer interactions by powering real-time chat, or integrating with messaging platforms like WhatsApp, or SMS.

In healthcare, an administrator can automatically reduce patient scheduling no-shows and generate appointment summaries. In financial services, an advisor can analyse client spending and savings history to offer personalised coaching and create tailored plans and goals.

The need for secure AI architecture

Any business’ AI strategy is only as good as its data strategy. Yet today’s customer data has never been more fragmented.

On average, organisations are using 1,061 different applications, yet only 29% of them are currently integrated.

What companies really want is one connected platform or one that will connect all of their data. In this era of AI, organisations need a customer data platform that acts as a single source of truth enabling them to drive business resilience, meaningful customer engagement, and future growth.

With a secure AI architecture, teams can benefit from generative AI without compromising their customer data, while at the same time letting companies use their trusted data to improve generative AI responses.

It’s crucial that AI recommendations are reliable, and that users are enabled to train models on their own data and validate these responses. Every effort to mitigate harmful outputs by conducting bias, explainability, and robustness assessments should always be a priority in AI.

By combining an integrated customer data platform with a conversational AI platform that draws on secure, trusted data, business leaders and their employees can be confident in making better, data-driven decisions.

The era of generative AI is just getting started, but the full potential of this technology’s benefits is yet to be realised.

There is so much promise and opportunity for businesses to gain real value and growth, ultimately giving employees and customers a better experience.

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