How technology and business leaders are using AI platforms

AI platforms: man standing in an office tapping a tablet in his hands

This is a guest IDC blog post sponsored by ServiceNow.

The focus on business transformation, growth, and resiliency using generative AI (GenAI) capabilities is at an inflection point for senior business and technology leaders, the C-suite, and boards of directors.

Leaders face difficult choices regarding models, data, security, user experience, ethical policies, and the overall business value of their AI investments. These decisions are fraught with business risks.

What's more concerning is that executives are spending valuable resources and time building models disconnected from the processes and business outcomes that GenAI is intended to improve. This disconnect is increasing business risks as models are being developed without the ability to become embedded into a system of action. Very soon, GenAI models will be built into a system of action.

Consolidated approach

GenAI models offer only limited business value when used and developed separately. Fortunately, a new approach that aligns people, processes, and GenAI technologies to optimise business outcomes is available: AI platforms.

Imagine an out-of-the-box employee, customer, or technology workflow that uses pre-integrated and pre-curated analytic models that are contextually aware of an organisation's data environment and business requirements.

Sophisticated GenAI models are embedded in its processes, enabling alignment and intelligence across teams, individuals, and process workflows. They produce an answer to a specific question or problem.

This level of ‘personalised AI’ uses intelligent design to create a new experience for technology teams, employees, and customers. This means that the data, the AI platform layer, and the workflow are all pre-curated out of the box, operating within the existing environment.

With such an implementation, executives can deliver cost optimisation and productivity outcomes across every process, team, and individual, recognising the critical desired business outcomes at the start of GenAI projects. This approach enables speed of implementation and time to value—and a transparent path towards value realisation.

Supercharged intelligence

The creation of GenAI strategies today must move from proof of concept to proof of profits through well-defined use cases and embedded GenAI capabilities. Competing effectively and efficiently in the future requires leaders to take pragmatic actions now to define their AI platform of the future.

To achieve optimised and sustainable business outcomes, GenAI technologies should be embedded into every process workflow. This approach enables organisations to have contextual awareness of all data to produce the most accurate and valuable outputs.

Processes can become more intelligent and automated while providing flexible levels of human involvement that meet every organisation at its comfort and maturity level.

As a result of business transformation, digital services are dependent on a vast array of integrated business and technology processes that deliver product innovation and customer experiences. When empowered with GenAI, these processes become supercharged with intelligence that can be adopted at the individual and team levels.

Smarter, cost-efficient decision-making allows teams to move faster with more accurate and correlated data from across the organisation. Traditional organisational and data boundaries disappear while business results become measurable and transparent, enabling more personalised technology team, customer, and employee journeys.

A new approach that aligns people, processes, and GenAI technologies to optimise business outcomes is available: AI platforms.

Optimised use cases

IDC suggests that technology executives consider creating concrete GenAI use cases, putting customers’ customer or employees at the heart, supported by core metrics and capabilities, such as ticket deflection, self-service, chatbots/virtual assistants, AI-driven search, and knowledge base summarisation.

These capabilities enable executives to measure the business value of their GenAI initiatives, facilitating short-term wins that fund longer-term business transformation.

Recent customer conversations with IDC focus on several areas where early embedded GenAI returns look promising, garnering strong executive-level funding and deployment support. Leaders should realise that the combination of data, a platform approach, process alignment, and trusted models are key foundational requirements for business value realisation.

Executives are moving forward with use cases such as the following.

An organisation wanted to remove manual processes for its service agents to improve utilisation and efficiency and to transform customer experiences. A major goal of the initiative was to develop innovative service management and customer communication practices across teams, processes, and outcomes.

The executive team knew that it had to move away from fragmented tools and processes. To do so, it established an AI platform-first approach to enable scale, speed, and smarter decisions.

The team also realised it had to consider both the processes it wanted to improve and the GenAI models as a single entity. To track outcomes and measure progress, the organisation’s tactics included:

In another example, a global customer had fragmented teams, tools, and processes that were inhibiting growth, limiting scale, and negatively affecting agent and customer experiences. Service operations were under pressure to scale faster to meet business growth and do more with less.

The company deployed embedded GenAI for predictive intelligence in core processes to identify forms more quickly for employees, thus accelerating time to resolution. This capability was augmented with a GenAI-powered virtual agent that answers questions using a unified knowledge base of third-party data sources.

Many of these processes have been redesigned, enabling faster responsiveness and the elimination of manual toil and low-value steps. The organisation has experienced a cascading value effect as agents and employees can return to work and solve problems faster, leading to exceptional customer experiences.

Some of the metrics used to measure business outcomes include:

For technology and business leadership teams, the time is now to use embedded GenAI across critical customer and employee workflows to create an AI platform for sustainable competitive advantage.

Message from ServiceNow

The age of AI-powered business transformation is just getting started. AI Pacesetters, as defined by the ServiceNow Enterprise AI Maturity Index, are pulling ahead of the pack—not only to reshape how work gets done at scale, but also to rethink how talent is developed and how AI progress is measured.

Pacesetters are embracing AI-embedded platforms, such as ServiceNow and its Now Assist offering, with built-in AI capabilities to span multiple business areas, break operational silos, connect data, and supercharge teams and functions.

Find out how ServiceNow helps organisations of all shapes and sizes put AI to work.