4 Questions on AI -Obase CEO Dr. Bulent Dal
Artificial intelligence has become one of the most important transformation areas on the corporate agenda. But today, the real question is no longer “Should companies adopt AI?”
The real question is:
How can companies turn AI into real business value?
In this interview, Dr. Bülent Dal, CEO of OBASE, shares his perspective on why AI projects struggle to move beyond the pilot stage, how Decision Intelligence, Agentic AI and AI Governance will shape the future of enterprise AI, and what will differentiate companies as we move toward 2030.
“AI is not a technology project. It is a transformation project.”
At the heart of this transformation lies something as important as technology itself: decision-making.
1. Why do so many AI projects struggle to move beyond the pilot stage?
[VIDEO 1 – Why do AI projects get stuck in the pilot stage?]
Organizations are making significant investments in AI. Yet many projects struggle to move beyond a successful pilot and deliver sustainable business value at scale.
One of the main reasons is that AI projects are often approached independently of the business processes and decisions they are meant to improve.
Before starting an AI project, organizations should ask:
Which decisions can we make better?
Which decisions can we make faster?
Which decisions can we automate or augment?
Technology alone does not create value. Value emerges when technology is connected to the organization's business processes and objectives.
That means AI projects should not be evaluated solely through technical success metrics. They should also be measured by their impact on tangible business outcomes such as cash flow, growth, customer acquisition, efficiency and corporate reputation.
Many projects fall into what can be described as the “pilot trap” because this connection is never fully established.
Real transformation does not come from successfully completing a pilot. It comes from making AI part of how the organization operates and makes decisions.
2. How will Agentic AI, Decision Intelligence and AI Governance shape corporate AI strategies?
[VIDEO 2 – Agentic AI, Decision Intelligence and AI Governance]
As AI continues to evolve, three concepts are becoming increasingly important: Decision Intelligence, Agentic AI and AI Governance.
Together, they represent three complementary layers of the transformation taking place in enterprise AI.
Decision Intelligence: From data to decisions
Decision Intelligence strengthens the journey from data to decisions.
Rather than simply understanding what happened, it helps organizations determine what decisions should be made based on the available data and business context.
Agentic AI: From decisions to action
Agentic AI takes this process one step further.
The goal is not only to generate recommendations or decisions, but to enable those decisions to translate into action autonomously.
AI agents can orchestrate tasks and processes around defined objectives, reducing the distance between decision and execution.
AI Governance: Making AI accountable
The third layer is AI Governance.
As AI takes on a greater role in business decision-making, control, transparency, security and accountability become increasingly critical.
The AI strategy of the future will therefore not be limited to building more powerful models.
Decision Intelligence will strengthen decisions. Agentic AI will turn decisions into action. AI Governance will ensure that this power is used in a controlled, transparent and accountable way.
Without these three elements working together, the potential of AI to create sustainable value across the organization is significantly reduced.
3. How can AI solutions create real value for organizations?
[VIDEO 3 – OBASE AIR and the business value of AI]
Traditionally, organizations have relied on reports, scorecards and dashboards to understand their data, followed by human interpretation and decision-making.
AI has the potential to take this process to a new level:
From data → to decisions → to action
This transformation is at the heart of the OBASE AIR approach.
The goal is not simply to analyze the data organizations already have, but to enable them to make better, faster and more decisions.
Data is becoming increasingly accessible. Organizations have more data than ever, while access to similar AI models is becoming easier.
As a result, competitive advantage will no longer come simply from which model you use.
The difference will come from how effectively a company can bring together:
- Data
- Business context
- Business culture
- Processes
- Business rules
and turn data into fast, accurate and impactful action.
This is why the success of an AI transformation cannot be measured solely through model accuracy or technical performance.
The more important question is:
How much does AI improve the quality, speed and volume of business decisions?
Because together, these three factors determine the value created for the organization.
4. What will be the biggest AI-driven shift in business by 2030?
[VIDEO 4 – The future of AI and business by 2030]
Looking toward 2030, one of the biggest shifts for organizations will be moving from simply having data to turning data into decisions and action.
That is why organizations should start asking themselves:
Not “What data do we have?” but “Which decisions should we improve, and what value should those decisions create?”
This changes where an AI transformation begins.
Decisions first.
Then the data required to support those decisions.
And around them: business logic, business context, processes and the AI capabilities required to bring everything together.
Because data is a necessary condition — but not a sufficient one.
Another important shift is that decisions can no longer be viewed within the boundaries of individual departments.
Consider a campaign decision. It can affect pricing. Pricing can affect supply. Supply can ultimately affect cash flow.
This means organizations need to move beyond optimizing individual departments and processes separately. Instead, they need to take a holistic view of interconnected decisions and processes.
By 2030, the companies that stand out will not simply be those using AI.
They will be the companies that integrate AI into how they operate, make decisions and create value across the organization.
The New Competitive Edge in AI: Decision-Making
The opportunity AI creates for organizations goes far beyond faster analysis or greater automation.
The real transformation lies in reimagining the journey from data to decisions and from decisions to action.
That is why organizations should put three questions at the center of their AI journey:
Which decisions should we improve?
How can we make those decisions faster?
How can we turn decisions into action?
The companies that turn AI into a competitive advantage will not simply be those investing in technology.
They will be the ones transforming the way they make decisions.
And perhaps the most important mindset shift in the age of AI is this:
Decisions first. Data second.