AI is transforming work for every company, across every industry, and in every function. Competitive advantage today is driven by adopting the right strategy, tooling and implementation.
In September, Salesforce revealed its new platform called Agentforce, which allows enterprise organizations to rapidly create and deploy their own AI agents alongside human co-workers.
Other enterprise software companies have followed suit indicating that tech giants are embracing a third wave of AI where autonomous AI agents will go beyond simply generating and analyzing content. Agents take on tasks on behalf of business workers, as chatbots and co-pilots did in the first and second waves.
Despite believing AI will be as significant to their businesses as the rise of the internet, more than half of AI projects led by CIOs don’t make it through to completion, either because they’re too expensive, don’t show ROI fast enough, or can’t be trusted with customers and sensitive data.
CIOs are currently faced with numerous hurdles when implementing AI, which is why so few have fully implemented the technology within their organization, citing an array of technical and organizational challenges, led by security and data infrastructure.
In fact, just 11% of CIOs — with their greater technical expertise and broader view of the organization — say they’ve fully implemented AI — 18 to 38 percentage points less than their line of business counterparts.
These security issues often revolve around unsanctioned AI in the workplace, which puts company data, systems, and business relationships at risk. This has been caused by the adoption of mass-market generative AI tools used by workers, which has ushered in a new era of “shadow AI”.
Shadow IT refers to software, hardware, applications and devices employees use that IT teams did not authorize. When there is a delay in adopting AI employees typically turn to external tools that they think can help them do their jobs better, which highlights the urgency of implementing trusted tools within the workplace.
To harness employees’ interest and enthusiasm for using AI in the workplace, without compromising data or security, CIOs need to act swiftly.
AI agents are the next frontier
No one has a greater influence on whether a firm is successful or not when it comes to AI implementation than the CIO.
However, building and rolling out AI-based systems can seem like a large and unwieldy project for CIOs, fraught with risks. AI agents are emerging as solutions to these challenges.
AI agents are pre-built and highly customizable, capturing the attention of technologists and their business leaders. They also use data to execute complex, multistep workflows and are capable of performing work with varying levels of autonomy.
Gartner predicts that by 2028, at least 15% of day-to-day work decisions will be made autonomously through agentic AI (up from 0% in 2024).
This is because AI agents can act as virtual workers who can carry out a series of tasks without supervision. They are touted as the next phase of AI and a major evolution of large language model-based AI from chat interfaces, operationalizing automation at a scale like never before.
By embracing an agent-first approach, every CIO can redefine their business operations and stay ahead – right now.
CIOs must champion scale, speed, and optimization of AI adoption
Scaling AI adoption in the enterprise must be a priority for 2025. CIOs are the most qualified business leaders to champion scale, speed, and optimization of AI implementation within a business.
However, our research also highlighted that CIOs often struggle to identify where to prioritize AI. Beyond the challenges of shoring up their data foundations, many CIOs are finding it difficult to define where and how AI should show up in their broader organizations.
To add to this, CIOs also feel uncertainty over how much budget to allocate toward AI in these early days of the technology. Only 47% are confident they’ve allocated the correct amount of budget to AI initiatives.
AI agents are now the number one choice for CIOs as they come pre-built, and can generate responses that are consistent with a company’s brand voice and guidelines using trusted business data.
Before setting out to deploy AI tools, specifically AI agents, CIOs should:
- Define clear objectives. Start by defining what you want to achieve with AI. Whether it’s reducing response times, enhancing customer satisfaction, or cutting operational costs, having clear objectives will guide your implementation process and help you measure success.
- Assess and prepare your data. AI agents rely on high-quality data to function effectively. Ensure that you have robust data collection and management systems in place. This includes customer interaction data, transaction histories, and other relevant information. Clean and structured data will enable your AI agents to provide accurate and relevant responses.
- Choose the right AI agent type. Select the type of AI agent that best fits your needs. For instance, if you need an agent to handle routine customer queries, a reactive agent might suffice. For more complex tasks, consider a goal-oriented or learning agent that can adapt to changing customer needs and provide more sophisticated support
- Upskill the workforce: Making AI work for workers requires leaders to reimagine how they develop and train every part of their organization. With perspectives and experiences of AI among desk workers varying so widely, a tailored approach to AI enablement is essential to setting every employee up for success.
Companies and their CIOs must get ready to implement fast as autonomous agents will become central to organizations’ customer engagement and experience strategies.
Businesses that quickly embrace this technology will be well-positioned to reduce costs while meeting the demands of today’s customers in a competitive global market.
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