Tapping AI for Enterprise Enablement Is Supercharging Corporate Capabilities

artificial intelligence

Reliable operational performance can’t be pulled out of thin air.

To play ball in today’s operating landscape, organizations need both a competitive position and a winning proposition, each underpinned by scalable, repeatable processes.

The rise of embedded artificial intelligence (AI) solutions that augment enterprise back-end workflows is increasingly transforming the way firms carry out processes at scale by providing a suite of solutions that are much faster, quicker, and often cheaper than humans.

While contemporary enterprises ingest vast volumes of data at a level never before seen in human history, innovative AI models let firms parse these torrential terabytes of operating information.

By uncovering trends and patterns that signal opportunity for better decisions and next actions, AI-assisted workflows let businesses identify change-the-game efficiencies that may have been blocked by traditional or manual approaches.

Already, industry-specific intelligent business applications are accelerating tasks with incredible speed and accuracy.

Still, at the end of the day, businesses looking to embed AI into the fabric of their daily operations need to ensure that they can onboard the technology without sacrificing convenience for security.

Read more: It’s 23-Year-Olds vs AI in the Latest Business Battle Royale

Capturing Efficiencies With AI Accelerations

The next generation of business growth will be driven by thoughtful, high-trust innovation as firms look to strike a compelling balance between machine speed and human judgment.

And with generative AI taking off exponentially, companies are already realizing labor- and cost-saving applications in every field, from healthcare to finance, according to “Preparing for a Generative AI World,” a PYMNTS and AI-ID research collaboration.

“We are in that economic cycle where every cost you can beat out of the process is necessary right now … how to save money and how to eliminate those manual steps in the processes is top of mind,” Ingo Money CEO Drew Edwards told PYMNTS.

To gain a competitive edge in today’s increasingly complex business environment, savvy organizations are integrating AI solutions that automate workflows and business processes, creating new programs that efficiently manage operational costs while improving performance.

And these AI applications are not just for customers — they’re often for the business itself.

“It’s everything from helping engineers write code faster to helping people internally understand the overall knowledge base at the company, and things like that,” Meta CEO and Co-founder Mark Zuckerberg said in discussing the back-end efficiencies of leveraging AI on his company’s most recent earnings call.

“We’re leveraging AI to move our systems towards using fewer larger models that enable us to leverage learnings across product surfaces and deploy improvements more quickly, broadly and efficiently,” Meta CFO Susan Li added.

While leaders have for the best decade-plus been able to deploy automated capabilities across core business functions to drive efficiency and business value at scale, firms looking to enhance their own workflows by integrating AI need to consider, right now, how they can employ generative AI in jobs to ensure it is a value-add.

PYMNTS research in the July 2023 report, “Understanding the Future of Generative Al,” a collaboration with AI-ID, revealed that LLMs — the neural networks behind OpenAI’s ChatGPT and Google’s LaMDA — could impact 40% of all working hours.

But it bears remembering that AI technology represents a capability phase shift — not a turnkey silver bullet solution to ongoing woes.

See also: How Truly Responsive and Intelligent AI will Change Business

Capturing Efficiencies Across Historic Cost Centers

In addition to AI’s promising greenfield opportunity areas within the enterprise back-end, the technology is also poised to revolutionize consumer-facing touchpoints across a swathe of sector agnostic engagements.

PYMNTS has previously written about how there exists a large and growing opportunity for businesses to leverage AI agents to respond to messages at scale, a traditionally labor- and cost-intensive process.

DoorDash is now testing an AI-based chatbot to enhance ordering and help customers find the food options that best suit them.

“AI enables us to optimize customer experiences, but all while minimizing fraud and compliance issues,” Andrew Stucchio of Discover Global Network told PYMNTS, while Olivier Thierry, chief revenue officer at HungerRush, told PYMNTS separately that voice AI is especially useful in pizza restaurants, where consumers disproportionately call in their orders.

“The technology is more accurate, efficient and consistent than many human employees,” Thierry said.

And AI-powered assistance is emerging at a critical behavioral inflection point where consumers are increasingly becoming more comfortable with voice assistants in their day-to-day lives. Data from PYMNTS’ study “ConnectedEconomy™ Monthly Report: The Evolving Digital Daily Edition” revealed that 86 million consumers now use voice assistants each month.

That’s why, as PYMNTS has written, once firms have a better idea of how to employ AI technology efficiently, they will be able to adapt and redesign jobs around that — all while realizing new efficiencies that drive cost out of the business.