Big Consulting's AI Bluff: Tech Companies Offer the Real Deal

Polarization is not just confined to tech, although it's cozy relationship with finance ensures that it is rapidly driving every market this way at the expense of the free market innovation that got us out of the caves in the first place. Thus cartels have formed , hollowing out the tax base, including the offshoring of the emerging jobs, which will not lead to growth in our western consumer based economies. Public spending or private spending is curtailed and inevitably built on debt rather than from the fruits of growth.

Even the big players are struggling for business in a risk averse world where corporations are akin to the Little Britain comedy defence 'computer says no'. Take the big consultancies who are increasingly being found out and suffering from Government and Corporation cuts. Post the digital transformation gravy train they are now buying their way into AI, while using offshore workers, to maintain their profits over the quality and privacy that bigger companies need. We need to use applied AI from product companies rather than using big consultancies who want to bill time and money. They can shout above the noise use their leverage to keep out agile tech led companies who use SLMs (specialized and small models) to deliver real benefit rather than fanciful ROI and high compute and energy bills.

5 Disadvantages of Using Big Consultancy Firms for AI Deployment

1. High Costs and Unpredictable Expenses: Big consultancy firms have high overhead costs and charge premium fees for their services even if they start out offering teaser intro rates. Their pricing structures are as complex as the Ts and Cs and involve hidden costs, making it difficult for companies to budget effectively for AI deployment.

2. Slow Turnaround Times and Lack of Agility: Large consultancies are often bureaucratic and can be slow to adapt to changing project requirements or market conditions. This can result in significant delays in AI deployment, potentially costing businesses valuable opportunities in today's fast-paced digital landscape.

3. One-Size-Fits-All Solutions and Limited Customization: Big consultancies tend to rely on standardized frameworks and methodologies that may not perfectly align with the unique needs of each client. Their focus on generic solutions can limit customization options, potentially hindering the effectiveness of AI implementation.

4. Lack of Focus and Domain Expertise: Big consultancy firms often cover a wide range of services and industries, which may dilute their expertise in specific AI domains. Their lack of deep focus and specialized knowledge can lead to suboptimal AI deployments and missed opportunities for maximizing business value. Look at the failure rate and headlines out there.

5. Potential Conflicts of Interest and Vendor Lock-in: Some large consultancies have financial relationships with specific technology vendors, which can create potential conflicts of interest when recommending AI solutions. Additionally, their reliance on proprietary tools and platforms may lead to vendor lock-in, making it challenging for companies to switch to alternative solutions in the future.

Why Applied AI from Tech-Led Companies is the Future for Large Enterprises

None of us are buying into the tech bro brand-washing any more. They keep asking for big cash to control the technology to maintain control until they come up with the winning formula. That money would better serve our economies within a competitive and free market that encourages innovation rather than denying it.

In the fast-paced world of never ending digital transformation, tired and sceptical enterprises are now seeking innovative ways to harness the power of AI. While big consultancies may offer alluring promises, tech-led AI product companies, specializing in applied AI solutions are emerging as the clear frontrunners in this space. These agile innovators prioritize speed, quality, privacy, and cost-effectiveness, outshining the traditional consulting model in many ways.

The Agility Advantage

Tech-led AI companies are built for speed. They operate within a nimble and agile approach, allowing them to rapidly develop and deploy AI solutions that address specific business challenges. This stands in stark contrast to the often cumbersome and bureaucratic nature of large consultancies, which can be slow to react to changing market conditions.

Quality and Privacy at the Forefront

Specialization is another key strength of tech-led AI firms. These companies typically focus on a specific domain or industry, allowing them to develop deep expertise and deliver tailored solutions. They prioritize data privacy and security, often utilizing specialized and small models (SLMs) that offer enhanced control and transparency. This focus on quality and privacy differentiates them from larger consultancies that may rely on offshore resources, potentially compromising data integrity and confidentiality.

Cost-Effectiveness

Cost-effectiveness is a significant advantage for tech-led AI companies. They offer competitive pricing models, often with subscription-based options that provide greater flexibility and scalability. This contrasts with the high fees and often unpredictable costs associated with big consultancies, which can strain even the most generous budgets.

The Rise of SLMs

Specialized and small models (SLMs) are becoming increasingly popular due to their ability to deliver precise and efficient results. They are ideal for handling sensitive data and can be customized to meet the specific needs of individual businesses. SLMs offer a compelling alternative to the large, generalized models often employed by big consultancies.

The Future of Applied AI

The future of applied AI lies in the hands of tech-led companies that prioritize agility, quality, privacy, and cost-effectiveness. While large consultancies may try to buy their way into this space, their lack of focus and commitment to offshore practices ultimately puts them at a disadvantage.

Large enterprises that choose to partner with specialized AI firms will reap the rewards of faster innovation, better data security, and more affordable solutions. As SLMs continue to evolve, we can expect even more exciting advancements in the field of applied AI. The time to embrace the future is now.

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Written by Neil Gentleman-Hobbs