Does your CIO look tired? Perhaps GenAI worries are keeping them up at night.
They certainly face a tough task. CIOs must figure out how to get the most out of the fast-evolving technology and generate business value. The pressure to deliver outcomes has resulted in a lot of trial and experimentation, but a road map for success hasn’t been easy to find, especially as use cases vary wildly depending on an organisation’s position on its AI journey.
However, new research from MIT’s Center for Information Systems Research suggests a process that could enable CIOs to succeed at the difficult juggling act of implementing AI into workflows quickly and safely.
The research was inspired by questions from CIOs and their peers on why they aren’t getting the same value from GenAI as they have from data and analytics technologies in the past. Based on a series of virtual roundtable discussions with data and technology executives, it identifies a need to separate the technology into two distinct parts – tools and solutions – before deploying them in a two-step strategy.
AI tools
AI tools “are designed to be broadly applicable”, according to Dr Nick van der Meulen, who co-authored the research. They could include conversational systems, such as ChatGPT, Claude or Gemini, as well as digital assistants embedded in existing productivity software.
“An employee will use a GenAI tool to summarise a document, brainstorm ideas, rewrite an email or analyse financial results,” says Van der Meulen. “As one executive in our study put it, they allow for ‘productivity shaves’.”
Crucially, the report reveals that AI tools also help employees get comfortable with using AI and are important mechanisms for building data democracy in an organisation.
GenAI tools can serve as a form of grassroots innovation. Employees can discover promising use cases that can later evolve
However, the report emphasises that CIOs must understand some basic principles of usage with this first step, most importantly putting in place certain guardrails and backing it up with workforce training.
“Unvetted GenAI tools, in the form of ‘bring your own AI’, can bring significant risks for an organisation, including data loss, intellectual property leakage, copyright violation and security breaches,” explains Van der Meulen. “The guardrails should outline which tools are acceptable and any conditions that may apply. For example, a company may permit GenAI tool use when prompts draw on publicly available information but disallow its use if prompts require company data.”
Employees shouldn’t be left to explore tools independently, according to the MIT research. There must be company-wide training in place to teach them how to effectively and responsibly instruct and interrogate GenAI tools so they can get the most out of them.
With these guidelines in place, CIOs can be assured that tools are being used safely. This will also help foster a self-perpetuating understanding of AI best practices across the organisation. As more staff use the tools correctly, best practices will become the norm.
AI solutions
Once a sound knowledge base has been established, CIOs can further build AI architecture and expand its horizons with the introduction of GenAI solutions, which help groups of employees to transform workflows and create value.
For example, Van der Meulen says the research team has “heard from a number of call centres that use LLMs to transcribe calls as they happen and process the content and tone of conversations. This is then used to coach agents in real time to either recommend empathetic responses to frustrated customers or propose upselling opportunities for satisfied ones.”
The key to success is to pursue both tools and solutions but use different strategies that dovetail to create a virtuous cycle.
“GenAI tools can serve as a form of grassroots innovation,” says Van der Meulen. “Employees can discover promising use cases that can later evolve into more formalised, scalable and lucrative GenAI solutions.”
Organisations at different stages of the AI journey must adopt different strategies. The report recommends that the best starting point for a GenAI journey is the targeted adoption of a few tools from trusted vendors, accompanied by close oversight.
Those further along in their journey should shift their focus to developing GenAI tools into solutions that contribute to strategic business objectives.
For instance, NN Group, an international financial services company, created a ChatGPT ‘playground’, where employees can use various GenAI tools to test their ideas on how to make their work more efficient.
“The playground is available to all employees. With a few ground rules in place and by making it easy to use, there is no need for employees to use unsupported tools outside of the playground,” explains Tjerrie Smit, NN Group’s chief analytics officer. “Launching the playground has been a game-changer for us. It provides a secure and compliant environment where our employees can safely experiment with GenAI. This proactive approach not only encourages innovation but also ensures that we can scale successful ideas into impactful AI applications across the organisation.”
Buy, boost or build?
One of the main takeaways from the research is that businesses can choose their approach: buying, boosting or building an AI solution.
Buying means using vendor-provided solutions where the vendor manages the model and operations. Boosting enhances vendor-provided models by incorporating proprietary data through techniques like fine-tuning or retrieval augmented generation (RAG), which customise pre-existing GenAI models with more relevant information from company sources. Building is the most resource-intensive approach, where organisations take full ownership of developing, running and maintaining the model.
“Buy or boost GenAI solutions when you need to move fast and gain competitive parity,” advises Van der Meulen. “But build when you need a differentiated GenAI solution that is hard to imitate and provides a competitive advantage.”
CIOs must remain vigilant when it comes to business alignment, so that GenAI is never siloed and left in the hands of a few select technologists, as this will starve it of the oxygen of innovation.
As the MIT research suggests, the surest way to accelerate GenAI’s value to an organisation and ensure it is safely embedded is to increase employee access to the technology.
