Generative artificial intelligence has taken the business world by storm in 2023 – and for good reason. From a digital transformation perspective, it has the potential to increase efficiency to new heights at a time when it is most needed.
Most of today’s attempts at digital transformation of enterprises fail. Recent Gartner report found that nearly 70% of CFOs believe that digital spending is not performing as expected. The main cause is the disconnect between those results and the software teams’ ability to deliver them. Planview independently ordered From Project to Product 2023 State of the Industry Report found that business leaders believe that IT teams tasked with digital transformation can deliver 10x more than their actual capacity. Only 8% of IT and software development plans in the end they are implemented, while 40% of work on digital innovation is in vain.
The simple answer to this inefficiency is disjointed and disparate data. Most organizations use a multitude of tools to deliver digital transformation at scale. From Jira and GitHub to GitLab and Azure DevOps, all of these systems play a key role in the entire software development lifecycle. But here’s the catch — none of them are integrated or aligned. Value streams with minimal interoperability cause bottlenecks that prevent digital transformation from succeeding. Data integration and harmonization is critical.
Enterprise digital transformation is approaching a new era of opportunity amid the rise of generative artificial intelligence. Because Generative Artificial Intelligence Large Language Models (LLMs) are domain-agnostic and system-agnostic, they have unmatched potential to minimize wasteful workflows when integrated with Strategic Portfolio Management and Value Stream Management technologies. The size of the global digital transformation market is expected to exceed $7 trillion by 2032. Even a 5-10% reduction in waste is more than enough to move the needle. Now is the time to act.
Integration: Semantic foundation of data
Effectively harnessing the power of generative artificial intelligence to reduce wasted work first requires a common semantic data layer. Merging data sets from heterogeneous systems into a normalized data platform creates an essential basis for optimizing the flow of value. Once that holistic data foundation is in place, organizations can construct instructions that train generative AI LLMs to generate impactful prescriptive insights, identify high-risk work processes, and refine resource allocation. This takes a lot of hard work out of the software team’s planning process, essentially automating core aspects of value stream management with AI-powered productivity.
Another recipe could be to identify different underlying dependencies between different products or project initiatives that cause significant delays — leading the organization to add direct resource capacity or rebalance capacity between teams based on emerging data. This level of acute data-driven decision-making in relation to capacity and allocation helps align financial investments with high-priority projects, accelerating time-to-market for initiatives with the highest return on investment.
Alignment: The Power of Convergence
Organizational alignment is critical to using generative artificial intelligence for digital transformation success. It is important to remember that technology is only as powerful as your ability to apply it. For generative artificial intelligence to effectively accelerate value, it must be eliminated “black box” that exists between business results and software development. The business and technology functions of the organization must work in harmony. By synchronizing all the tools, processes, and metrics associated with software development and delivery, organizations can optimize decision-making across portfolios, value streams, and DevOps teams to connect digital transformation capital allocation with impactful business results.
This is where converging objectives and key results (OKRs) through strategic portfolio management, value stream management and agile planning are worth their weight in gold. It doesn’t matter how brilliant AI’s generative instructions are – they are unable to achieve the desired results and drive digital transformation without a shared overarching mission. Universal alignment bridges the gaps between the technology and business aspects of an organization with real-time visibility that delivers more intelligence, predictions and prescriptions. By integrating these actionable insights from portfolio management, agile enterprise planning and value stream management into a single source of truth, a system of record, cross-functional teams have a clear roadmap for turning ideas into results.
It’s no secret that the ongoing generative AI hype over the past 10 months has raised legitimate concerns about its ability to replace human workers in a variety of industries. However, in the context of digital transformation, we should not think about the future with a narrow “man or machine” mindset. It’s really about the people plus machinery. Applying AI-based technology to augment manual workflows is what will have the biggest impact on digital innovation in the years to come.