Decidr

In the realm of modern business operations, there have been three significant eras to date.

1. The Management Era

This was characterised by structured management theories championed by prestigious MBA programs from the likes of Harvard and Stanford.

The primary focus was on developing standardised strategies, processes and reporting methods.

However, this approach often resulted in a ceiling effect, where improvements were limited by individual managerial skills, restricting broader organisational growth.

2. The Consulting Era

Business consulting brought sophisticated strategies to the corporate world, with firms like McKinsey & Company at the forefront.

They offered bespoke solutions that were typically only accessible to big budget organisations due to their high cost.

While effective, the reach of these strategies was often limited, preventing smaller businesses from accessing top tier managerial insights.

3. The SaaS and RPA Era

The digital transformation led by SaaS companies such as Salesforce and Hubspot aimed to digitise specific business functions and connect legacy systems.

These tools democratised access to technological improvements and enhanced specific areas of business operations at a lower cost compared to in-house development.

However, their impact was often compartmentalised.

The Generative Era: A bizOps transformation

With the growing popularity of GenAI, we've entered a fourth era of business operations. In November 2022, the release of ChatGPT kicked off the GenAI arms race. Within months, big tech companies were scrambling to release competitors. These have largely been designed to slot into existing software, with mixed results.

Taking Google’s Bard as an example — company employees voiced concerns around its accuracy and effectiveness at launch in 2023. The company made the decision to rebrand the entire ecosystem to Gemini by the end of the year.

The trickle down effect has been a resounding sense of FOMO within the business landscape, particularly the 80% of Australian small businesses that are yet to adopt. Even issues with problematic search results, hallucinations and lawsuits haven’t stopped the consistent rollout of GenAI products.

A plethora of think pieces published across the media, Substack and LinkedIn have evangelised the productivity and fiscal gains offered by this “new” and exciting technology.

Of course, it isn’t actually new. AI has been around for over half a century. And plenty of traditional technology businesses and startups were developing in this space long before OpenAI went live.

Still, the release of ChatGPT rendered AI pervasive in a way that it hadn’t been before.

It was accessible and cheap — at least at an individual level. Those with little experience could fire up a public chatbot and play around. Those with more technical know-how could access open source software to create their own GPTs and platforms.

Fast forward to 2024 and AI is mainstream, particularly in the business space. The AI industry is projected to reach US $184 billion this year, with an annual growth rate of 28.46%.

Most tech companies operating in this space already have Pro or Enterprise offerings, recognising that this is where the opportunity truly lies.

A 2024 study from Slack’s Workforce Lab revealed that 60% of Australian executives have a high degree of urgency attached to AI implementation within their companies.

However, the same study showed that only 35% of employees receive guidance from executives regarding AI implementation. The expertise simply isn’t there.

This has left a lucrative opportunity for SaaS and big tech businesses to offer AI solutions to these businesses, most of which are marketed as ways to improve existing processes.

But that’s the wrong way to think about it.

Going beyond legacy systems will be essential for future businesses

GenAI isn’t something to be retrofitted — it has the power to crack open every aspect of business operations for improvement. But we can’t do that by treating the generative era as SaaS 2.0.

It's a mistake to try and hamfist this technology into legacy systems that are often rigid and not designed to accommodate the flexible nature of GenAI. This results in a narrow approach with siloed solutions for each problem. It's also not cost effective or efficient.

The integration of GenAI into business operations should signal a departure from the traditional. It's not a mere upgrade to existing technologies but a fundamental rethinking of how business operations can work.

To fully leverage its capabilities, companies must reevaluate, and in some cases redesign, their technological infrastructures to be as agile and scalable as AI systems themselves.

This shift may involve significant changes in corporate culture, processes and technology stacks to ensure seamless integration and maximisation of GenAI’s benefits.

The biggest roadblocks to these overhauls are expense and expertise. Decidr not only fills those gaps, it connects them.

Rather than try and solve siloed operational tasks with AI solutions, it integrates business data to train thousands of micro roles that can handle most digital tasks.

These include:

• Accounting & payroll
• Email marketing
• eCommerce
• CRM
• ERP
• Data & product intelligence
• Custom AI models

These networked agents operate against a common and controlled set of goals, reducing the need for third party tools and extra support staff. Most importantly, the platform is available to businesses of all sizes, but without the enterprise price tag.

This shift towards a broader application of AI is not merely beneficial but essential for businesses aiming to stay competitive in a data driven world. Modifying old systems with narrow AI doesn’t have long term viability.

Our vision for AI allows companies to be more adaptable, innovative and ultimately successful. It doesn’t just update business operations, it redefines them.