Generative AI (gen AI) is transforming how companies operate by creating original content such as images, text, videos, code, and audio. Organizations across industries are exploring or already using this technology to boost efficiency, improve customer experiences, and gain a competitive edge. But despite high expectations, many are still in early stages—and to make real progress, they must embrace change, manage risk, and build a strong foundation.

Gen AI: No Longer Optional

According to Abid Rahman, Senior VP of Innovation at Eversana, ignoring gen AI isn’t an option anymore. “If you’re not exploring it, you’re falling behind,” he says. This urgency is echoed in a June 2024 Harvard Business Review Analytic Services survey of 257 professionals involved in AI decisions. It found that while 60% of organizations see gen AI as a priority, only 48% feel ready to adopt it. A whopping 83% agree that companies risk being left behind without it.

What’s Holding Businesses Back?

The biggest barrier to gen AI adoption? Risk—legal, ethical, cybersecurity, and customer trust. About 56% of survey respondents cited these concerns as the main challenge. Thibault Main de Boissière, from Canva, emphasizes the need to carefully manage risks while staying agile. He recommends a strong feedback loop where companies test ideas, get user input, and measure performance continuously to ensure progress and stakeholder confidence.

Moving Forward Step by Step

Organizations are taking different paths to prepare. Eversana, for example, focuses on training, governance, and empowering internal teams. Employees were given clear guidelines about how to use gen AI responsibly, especially in regulated sectors like pharmaceuticals. An internal AI council helps review and fund promising use cases.

At Restworld, a job-matching platform in Italy, the team hosted AI workshops to make sure everyone understood the technology. Gen AI now helps their recruiters match candidates more effectively and even handles initial job-seeker conversations via WhatsApp. This shift has saved the company time and money—up to 20% in recruitment costs.

Progress Is Slow but Steady

While enthusiasm is high, only 16% of surveyed organizations have full-scale gen AI applications. Around half are still exploring or planning their strategy. Readiness is uneven—just 32% to 54% say their company is “prepared” in key areas like skills, infrastructure, and risk management. In fact, more companies feel unprepared than prepared in most categories.

Despite these challenges, most companies are actively improving their infrastructure (53%), creating governance policies (53%), updating processes (35%), and investing in employee support (31%).

Trust, Oversight, and Experimentation

Human oversight remains a crucial part of responsible AI. Dom Scandinaro, CTO at Cameo, says they use gen AI to summarize customer reviews on celebrity profile pages, but human editors always check outputs for consistency and accuracy. Gen AI models can still “hallucinate” or produce outdated results, so Cameo trains its AI using real customer input to keep the data fresh and relevant.

Early Benefits Are Already Clear

Companies like Canva have seen an increase in the number of features they can offer. For example, their “Magic Design” tool allows users to generate a complete design from a simple prompt. While some features are still evolving, the ability to create over a billion images shows how popular—and powerful—gen AI tools can be.

Similarly, Restworld has used gen AI to shift recruiters’ roles toward more analytical tasks. Instead of interviewing every candidate, recruiters now supervise AI-driven chats. This has allowed the company to cut thousands of manual conversations and redirect resources more effectively.

Goals and Expectations

Among those moving forward with gen AI, top goals include improved productivity (63%), employee efficiency (63%), innovation (48%), customer experience (45%), cost savings (44%), and competitive edge (43%). The potential is massive, and some are already seeing measurable benefits.

Best Practices for Gen AI Success

Organizations that are finding success with gen AI tend to follow a few key strategies:

• Executive leadership is crucial. Rahman stresses that AI adoption needs support and investment from top leaders.
• Build continuous feedback loops. Canva’s Main de Boissière notes that traditional testing methods don’t always work with gen AI. Ongoing evaluation is key.
• Be agile and fail fast. Cameo experiments quickly to find what works and stops what doesn’t.
• Choose the right partners. Long-term alignment, technical credibility, and cultural fit all matter when picking tech collaborators.
• Learn from others. As Conte from Restworld puts it, “Everyone is new to gen AI.” Sharing ideas and mistakes with peers can accelerate learning.

Looking Ahead

Despite the hurdles, the future of gen AI is bright. Most survey participants agree that the benefits outweigh the risks. They also acknowledge that having clear principles and governance is essential to move forward safely.

Ultimately, the greatest value of gen AI might lie in how it reshapes the way we work. “It’s a superpower,” says Rahman. “It lets people do things they couldn’t do before—faster and better.” But to truly unlock that power, organizations must go beyond just using the tools. They must rethink old processes, encourage innovation, and imagine new ways of working altogether.Thank you for your AI interest – please join our mailing list using our Contact Us page and Support Forum Registration page