By: Walter Pasquarelli, an expert advisor on AI strategy, data governance, and digital transformation
It’s been nearly a year since generative AI (gen AI) captured the public’s imagination. Initiated by the public release of ChatGPT, OpenAI’s chatbot, organizations are now looking towards a new era of productivity and efficiency. To put this opportunity in numbers, Goldman Sachs projects that if implemented judiciously, generative AI could add up to 7% to global GDP by 2030. Similarly, McKinsey estimates that the technology could add between $2.6 - 4.4 trillion USD annually across key industries.
To date, the primary advantages of generative AI for businesses are twofold: the capacity for efficiency gains and scalability, as well as accelerated content production (think of a text generator helping a marketing executive to overcome writer’s block).
But as the saying goes, whilst the future is already here, it’s not evenly distributed yet - which is certainly the case for generative AI. Technological hype cycles usually follow a process of excitement, reckoning, and ultimately adoption. The buzz around the potential benefits of generative tech abounds, but large-scale implementers remain few and far between. As technological, geopolitical, and economic dynamics are ushering us into the age of AI, businesses are in urgent need of understanding how to adopt the technology safely. This blog lays out five key steps followed by gen AI adoption pioneers.
Step 1: Demystify AI across your organization.
A quick Google image search with the term “generative AI” yields a mix of flying wired brains or futuristic robots. Though regrettably or not, AI is primarily based on statistics with computing power. Understanding precisely what the technology is about, what it can and cannot do, as well as how it may evolve, forms the foundation of any discussion surrounding gen AI adoption. To achieve this, practical approaches may involve expert workshops as an initial stepping stone, to more formalized company-wide Gen AI Task Forces composed of internal and external experts demystifying the technology across business units.
Step 2: Always start with the use case.
Generative AI is a powerful technology, yet broadly casting a neural network across your entire business is unlikely to increase revenue. Successful gen AI adoption hinges on an intimate connection to the overall business strategy. As we align gen AI efforts to business goals, we start to better understand how the technology can support in achieving the most vital KPIs and, in turn, identify business areas best left untouched. Run the counterfactuals, think of the art of the possible and pose “what if” questions on how implementing gen AI may improve your team’s operations. This systematic approach will yield the use cases and areas to further explore and trial out gen AI tools.
Step 3: Conduct a reality check of your capabilities.
After identifying use cases, it is time to conduct a reality check on the businesses' capabilities for gen AI adoption. For most organizations, these constraints manifest in their digital maturity levels, typically falling into two main buckets:
- Data and infrastructure. Data forms the building block of AI. Without clean, high-quality, and organized data, AI adoption becomes significantly harder.
- Talent. The talent pool that businesses have at their disposal, which ultimately engineer, fine-tune, and adapt gen AI tools.
While digital laggards will encounter difficulties adopting generative AI across their enterprise, they are not necessarily a lost cause. Talent shortages can be remedied through external developers, and likewise, data shortcomings can be supplemented by third-party contributions. Yet, improving and maintaining digital maturity takes precedence for organizations seeking to implement gen AI at scale.
Step 4: Pilot with Precision.
Pilot projects are a launchpad for wider gen AI implementation, serving as crucial testing grounds for strategic advancement. Piloting specific use cases provides invaluable insights into the practical utility of gen AI projects before making resource-intensive commitments. Controlled pilots perform the vital task of helping identify challenges early on and create internal expertise guiding informed scaling decisions. They ensure harmonization with the business strategy, gradual adjustment, and minimal operational disruptions during expansion. Particularly within project management, but most importantly, pilot projects are the vanguards for establishing initial organizational success stories for gen AI adoption. These, in turn, are crucial for building momentum and securing buy-in from senior stakeholders.
Step 5: Safeguard trust throughout your gen AI journey.
Any gen AI project can only thrive if trust in the transformative potential of the technology is established - extending across both international business units and customers. It comes as no surprise that employee resistance - stemming from fears of automation and ethical concerns catalyzed by AI - are the main blockers of tech adoption. Yet, studies also underscore that customers view responsible AI policies and development as sources of competitive advantage. To secure the successful adoption of gen AI across your enterprise, products and services, organizations should institute internal policies setting out ethical and transparency requirements, as well as making early stakeholder engagement a foundational pillar of gen AI adoption.
How is Deltek Adopting Generative AI?
Deltek’s Vice President of Product, Bret Tushaus, offered his views on generative AI and how Deltek is working with this emerging technology. Bret commented, “The 5 steps outlined here are precisely what organizations should be doing to reap the value generative AI can yield. Furthermore, they also closely align with how Deltek is approaching generative AI within our own product portfolio.”
Bret also expanded on this to talk about how Deltek is looking to use gen AI to make its products even more valuable for users, “We have worked hard to demystify and get a true understanding of how the technology could benefit our customers and determine where Deltek’s capabilities are ripe for the use of the technology. We have focused heavily on identifying relevant use cases and have instituted pilots to focus in on generative AI driven features that are purposeful in nature and produce true value for our customers. And, of course, we are keeping a close eye on doing this in a way that honors the privacy of our customer’s data and delivers the associated functionality in a responsible way.”
All of this creates exciting opportunities for gen AI to fuel Deltek’s ability to enhance its solutions through content generation, enabling better informed decision making, prescribing proactive actions and automating for efficiency.
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About the Author
Walter Pasquarelli is an expert advisor on AI strategy, data governance, and digital transformation, advising Google, Meta, Microsoft, and presidencies and governments internationally.
Leading advisory and editorial programs at The Economist Group, Walter operated at the forefront of technological innovation, shaping policy and business perception of emerging technologies. He led the development of the first globally focused "AI Index", benchmarking countries' readiness to uptake emerging technologies across key industries and markets.
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