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It’s no secret that AI applications have been gaining traction across nearly all industries. Technology advancements and cost reductions means that today’s Large Language Models (LLMs) can ingest larger amounts of data than ever before, making them more accessible for projects like code development, content generation and more.
The abilities of AI technology and the general sentiment around these tools are changing almost too fast for many to keep track of. Even as the market has exploded, several high-profile articles and studies have emerged stating that a number of AI projects aren’t producing a return on investment.
Does this mean organizations should stop investing in AI projects? Of course not. Improving the digital customer experience is still important for nearly everybody. Customers still expect seamless experiences from the brands they work with. And according to CMSWire research, 89% of survey respondents call DCX either “extremely” or “very” important to their organization — a 9% increase over last year.
Further, employees still need better ways of working. And according to recent Reworked research, 82% of survey respondents call the digital workplace either a “critical” or a “high” priority for their organizations.
But perhaps leaders need a reframing of what they expect from their new AI initiatives. And there’s plenty of opportunities for success with AI initiatives — if leaders are intentional about when they’re trying to accomplish.
To further explore the current state of AI, its implications on organizational processes and how organizations should be thinking about AI initiatives to ensure success, CMSWire spoke to Gabe Aguilo, VP Innovation at Acquia. The conversation emphasized the importance of data governance and the potential for AI to transform various industries.
Table of Contents
- Data Is More Valuable Than Ever
- Strategic Decision-Making Evolves, But Strategy Is Still Critical
- Reframing the AI Conversation: Augmentation Over Replacement
- It’s Possible To Keep Up by Prioritizing Data
Data Is More Valuable Than Ever
What’s the quality of your data? These days, data is valuable because it drives business outcomes, efficiency and innovation — especially in AI and digital experiences. The organizations with high-quality data can better understand their users, personalize experiences, improve business efficiency and power AI models to generate insights, automate processes and accelerate development faster than they could before.
In specific industries, such as healthcare or finance, good data is essential for compliance, privacy and delivering better customer/patient outcomes. The organizations that manage, structure, and leverage their data effectively by optimizing it for AI ingestion can achieve a significant competitive advantage.
Optimizing the Customer Experience for Today’s Customer Behaviours
One of the reasons organizations need optimized data is because the way customers search for information is changing. While Google may still command more than 93% of all search traffic, not everyone is searching through a search engine these days. Algorithm-based apps and LLMs are causing the biggest upheaval in more than 3 decades around how the world searches for information on the internet.
“The reality is that new generations just aren’t using Google,” Aguilo said. “They’re using TikTok or answer engines to find answers. If you want your company to be discoverable, you need your data in a good place to be readable by those machines.”
Ensuring key information about your organization is findable is a part of delivering frictionless experiences. Your website might not be the front door to your business anymore, but customers still want information and it’s important to meet them where they are. “Acquia is committed to ensuring that information and content in its Cloud CMS platform in an Open system, ensuring that the content deployed is able to be accessed via humans accessing a website, or designed to be read by agents in a machine-friendly format,” said Aguilo.
Strategic Decision-Making Evolves, But Strategy Is Still Critical
The pace of change around AI means that AI is now doing things it couldn’t do even a year ago. A year from now, the technology will evolve further. For example, AI is moving beyond task automation to offer predictive analytics and operational insights that influence C-suite decision-making. However, AI doesn’t replace human strategy, but rather acts as an accelerator, one which requires human oversight and decision-making. “Any project involving AI requires sign off, review and an understanding by the business of how the tool will be implemented, either in-house or facilitated through an agency,” Aguilo said.
It’s important to maintain operational fundamentals even as leaders are challenged to rethink traditional management models. Data privacy, bias mitigation and transparency remain essential considerations as AI adoption accelerates. Organizations must take particular care with their data, to ensure that private data stays private. “One of the things I see many leaders asking about is the ability to turn their AI off," Aguilo said. “They want to ensure that their data isn’t being trained for other purposes.” This aligns with recent MIT research, where nearly 70% of leaders called “clear data boundaries" one of their deciding factors when choosing a gen AI vendor.
Reframing the AI Conversation: Augmentation Over Replacement
The use of AI tools can bring about a number of process efficiencies. This is already happening in many organizations. According to a recent Mckinsey survey, 21% of respondents whose organizations use gen AI say their organizations have fundamentally redesigned at least some workflows.
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As with any technology that improves processes, there’s a fear that AI will displace jobs. While these fears are valid, successful AI projects require human oversight, while successful AI tool adoption frees humans from the low-hanging fruit of routine tasks.
Despite concerns about job displacement, AI works best when it’s positioned as a tool to augment human expertise rather than replace workers. When applied to healthcare, the technology aims to free clinicians from routine tasks, enable more direct patient care and give patients a more consumer-friendly portal experience. Beyond healthcare, AI can bring about process efficiencies and information discovery to the people looking for information related to your brand or service.
It’s Possible To Keep Up by Prioritizing Data
The rapid pace of change means that businesses need to adapt quickly to new technologies and vendor assessments. Successful AI implementation requires clear metrics and outcomes, which align to business goals.
The future of IT will combine human expertise with machine precision in customer-centric operations. The leaders who will deliver successful AI initiatives will be those who focus on delivering frictionless experiences to their customers and employees.
Part of the strategy that Aguilo is actively developing at Acquia is being able to make the most out of the data that is already available in the organisation, tying together previously disparate systems into cohesive workflows. For Acquia, this includes leveraging data for customers outcomes across the Acquia Source CMS, Acquia DAM (Digital Asset Management) and Acquia CDP. This is critical as it respectively provides AI with the content, the asset (such as images or videos) and customer journey, to achieve meaningful cross-product outcomes that were previously manual.
At the end of the day, Aguilo doesn’t believe AI implementation is much different from other tools organizations have deployed. “I think you still have to be rooted in the same processes that you did before. You have to go through vendor assessment. You've got to understand the security and privacy concerns. You have to understand how the technology is deployed.”
This might be challenging if you don’t have a formal structure in place. But the organizations with a clear vision and goals will be able to make the most out of their AI initiatives.
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