By Chandra Sinnathamby
Leveraging generative AI to drive content innovation and efficiency conversations with CMOs, CIOs, and other high-level decision-makers consistently revolve around two critical questions: “How can generative AI benefit our business?” and “When will we see returns on our investment?”
While many leaders across industries report running numerous parallel pilots, many firms are experimenting with generative AI, but few have completely recognized AI’s potential for their business. A recent Digital trends study found that only about a quarter of senior executives believe their company has successfully integrated generative AI with their broader goals for customer experience and digital transformation. Nearly half the respondents report that this integration is still a work in progress (45%), and roughly a third haven’t even rolled up their shirt sleeves and gotten to work on this opportunity.
Despite these challenges, marketing leaders remain enthusiastic about the potential of generative AI to address their teams’ challenges. Often, their primary focus is content. India is at the forefront of generative AI adoption in the Asia Pacific region, according to a Deloitte report. With 83% of employees actively using GenAI, the country’s tech-savvy younger generation is driving this technological revolution. The widespread adoption is significantly enhancing productivity, with Indian users saving an average of 7.85 hours per week. As enterprises integrate GenAI into their operations, the potential for efficiency gains and skill development is immense, presenting both opportunities and challenges for employers in a rapidly evolving digital landscape.
Operationalizing generative AI for content personalisation
CMOs aim to expand and scale personalisation efforts but often find the breadth and depth of content to be a significant blocker. Additionally, global businesses need to run marketing efforts across multiple markets, but regional teams often lack the resources and budgets to effectively localize content. There is also a -growing need to frequently refresh content to stay relevant on crowded channels like social and paid media, recommending biweekly or even weekly updates.
Content demand is skyrocketing, outpacing the capabilities of traditional marketing structures. Teams are struggling to meet the ever-increasing need for fresh, engaging material within existing constraints. The current setup of segregated creative units, agencies, and suppliers lacks the agility and resources to produce content at the required velocity, volume, and cost-effectiveness. This mismatch between demand and capacity is creating significant challenges for marketing departments across industries. Generative AI has the potential to transform content creation, enabling productivity improvements of 10–100 times or more for certain workflows. These substantial gains can translate into higher-performing campaigns, faster time to market, and reduced costs. The challenge, and opportunity, lies in operationalizing generative AI for content across the enterprise.
Five strategies to transform generative AI from experimentation to real-world application
Enterprises need to modernize their approach to content and adopt a holistic strategy.
Enhance Creative Teams’ Capabilities
AI-powered creative tools boost productivity by speeding up ideation and tasks like image editing. This acceleration frees up creatives’ time, allowing them to take on more projects and explore new creative avenues. To maximize impact, seek AI models and solutions that integrate with the tools creative teams use every day, reducing steps instead of adding them.
Enable Marketers to Create and Remix Content
Typically marketers do not create media content; they develop campaign briefs and then hand them over to creative teams. With AI-driven creative tools, a significant portion of the content marketers need can become self-service. Content adaptation becomes streamlined as marketing teams leverage existing materials for localized modifications. This approach allows regional units to efficiently customize offers and refine content to suit their specific market needs.
Automate Manual and Repetitive Tasks
Organizations spend significant amounts on producing asset variations and editing content in post-production. AI-powered tools streamline campaign asset creation, generating thousands of variations for diverse channels, audiences, and products. These solutions integrate generative and creative APIs into workflows, automating routine image tasks efficiently.
Maintain Brand Consistency
For generative AI to be deployed at scale and help organizations differentiate, it must generate content consistent with the brand. When evaluating generative AI content solutions, choose those that allow customization of generative models to match the brand’s unique style and voice
Select Technology Designed for Business Safety
To move beyond experimentation, business need confidence that their AI solutions will not expose them to legal or security risks. Be intentional in selecting generative AI solutions designed to create content that is safe for use in commercial use, ensuring it does not violate third-party copyrights. Businesses must also ensure their data is protected and not used to train other companies’ AI models.
Brands implementing these strategies are already seeing pronounced benefits including. As the demand for content expected to rise five-fold in the next few years, organizations will benefit from moving generative AI out of the experimentation and into production today.
The author is director, digital media B2B strategy and GTM, Asia-Pacific, Adobe. Views expressed are personal and not necessirily those of financialexpress.com.